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) | 0 |
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) | |
Nouveau modèle de contenu (new_content_model) | wikitext |
Ancien texte de la page, avant la modification (old_wikitext) | |
Nouveau texte de la page, après la modification (new_wikitext) | As expected, the non-linear deep learning strategies outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are an alternate payment methodology which will change intermediaries with cryptographic strategies and needs to be embedded within the research areas of SIGeBIZ and SIGSEC. On this paper we propose to treatment this drawback through the use of the strategies originally developed for the pc-aided evaluation for hardware and software systems, specifically those primarily based on the timed automata. In this paper we introduce a software to review and analyze the UTXO set, together with an in depth description of the set format and performance. This paper provides an evaluation of the present state of the literature. This systematic literature evaluation examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know every part you need to have the ability to separate fact from fiction when studying claims about Bitcoin and other cryptocurrencies. We present the time-varying contribution ui(t) of the primary 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 high, fluctuating around (see Fig. 5), possibly a results of transactions taking place between addresses belonging to a couple fanatics trying out the Bitcoin system by shifting cash between their own addresses.<br><br>My website :: [http://haoyangzy.com/home.php?mod=space&uid=33985 http://haoyangzy.com/home.php?mod=space&uid=33985] |
Diff unifié des changements faits lors de la modification (edit_diff) | @@ -1,1 +1,1 @@
-
+As expected, the non-linear deep learning strategies outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are an alternate payment methodology which will change intermediaries with cryptographic strategies and needs to be embedded within the research areas of SIGeBIZ and SIGSEC. On this paper we propose to treatment this drawback through the use of the strategies originally developed for the pc-aided evaluation for hardware and software systems, specifically those primarily based on the timed automata. In this paper we introduce a software to review and analyze the UTXO set, together with an in depth description of the set format and performance. This paper provides an evaluation of the present state of the literature. This systematic literature evaluation examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know every part you need to have the ability to separate fact from fiction when studying claims about Bitcoin and other cryptocurrencies. We present the time-varying contribution ui(t) of the primary 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 high, fluctuating around (see Fig. 5), possibly a results of transactions taking place between addresses belonging to a couple fanatics trying out the Bitcoin system by shifting cash between their own addresses.<br><br>My website :: [http://haoyangzy.com/home.php?mod=space&uid=33985 http://haoyangzy.com/home.php?mod=space&uid=33985]
|
Lignes ajoutées lors de la modification (added_lines) | As expected, the non-linear deep learning strategies outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are an alternate payment methodology which will change intermediaries with cryptographic strategies and needs to be embedded within the research areas of SIGeBIZ and SIGSEC. On this paper we propose to treatment this drawback through the use of the strategies originally developed for the pc-aided evaluation for hardware and software systems, specifically those primarily based on the timed automata. In this paper we introduce a software to review and analyze the UTXO set, together with an in depth description of the set format and performance. This paper provides an evaluation of the present state of the literature. This systematic literature evaluation examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know every part you need to have the ability to separate fact from fiction when studying claims about Bitcoin and other cryptocurrencies. We present the time-varying contribution ui(t) of the primary 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 high, fluctuating around (see Fig. 5), possibly a results of transactions taking place between addresses belonging to a couple fanatics trying out the Bitcoin system by shifting cash between their own addresses.<br><br>My website :: [http://haoyangzy.com/home.php?mod=space&uid=33985 http://haoyangzy.com/home.php?mod=space&uid=33985]
|
Horodatage Unix de la modification (timestamp) | 1647699973 |