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 strategies outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are an alternative payment methodology which will replace intermediaries with cryptographic strategies and must be embedded within the research areas of SIGeBIZ and SIGSEC. In this paper we suggest to treatment this drawback through the use of the methods initially developed for the pc-aided evaluation for hardware and software program techniques, particularly those primarily based on the timed automata. In this paper we introduce a instrument [https://uchatoo.com/post/123406_https-www-analyticsinsight-net-where-to-buy-bitcoin-2022-defending-the-privacy-o.html where to buy bitcoin] study and analyze the UTXO set, along with an in depth description of the set format and performance. This paper provides an evaluation of the current state of the literature. This systematic literature assessment examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know all the pieces you need [https://yogicentral.science/wiki/We_Investigate_The_Risk_Of_Bitcoin where to buy bitcoin] have the ability to separate fact from fiction when reading claims about Bitcoin and other cryptocurrencies. We show the time-various contribution ui(t) of the first six base networks on determine 2. In most cases, ui(t) features a couple of abrupt changes, partitioning the historical past of Bitcoin into separate time durations. In the initial phase is high, fluctuating around (see Fig. 5), probably a result of transactions taking place between addresses belonging to a couple lovers trying out the Bitcoin system by shifting money between their own addresses. |
Diff unifié des changements faits lors de la modification (edit_diff) | @@ -1,1 +1,1 @@
-%About_Yourself%
+As anticipated, the non-linear deep learning strategies outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are an alternative payment methodology which will replace intermediaries with cryptographic strategies and must be embedded within the research areas of SIGeBIZ and SIGSEC. In this paper we suggest to treatment this drawback through the use of the methods initially developed for the pc-aided evaluation for hardware and software program techniques, particularly those primarily based on the timed automata. In this paper we introduce a instrument [https://uchatoo.com/post/123406_https-www-analyticsinsight-net-where-to-buy-bitcoin-2022-defending-the-privacy-o.html where to buy bitcoin] study and analyze the UTXO set, along with an in depth description of the set format and performance. This paper provides an evaluation of the current state of the literature. This systematic literature assessment examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know all the pieces you need [https://yogicentral.science/wiki/We_Investigate_The_Risk_Of_Bitcoin where to buy bitcoin] have the ability to separate fact from fiction when reading claims about Bitcoin and other cryptocurrencies. We show the time-various contribution ui(t) of the first six base networks on determine 2. In most cases, ui(t) features a couple of abrupt changes, partitioning the historical past of Bitcoin into separate time durations. In the initial phase is high, fluctuating around (see Fig. 5), probably a result of transactions taking place between addresses belonging to a couple lovers trying out the Bitcoin system by shifting money between their own addresses.
|
Lignes ajoutées lors de la modification (added_lines) | As anticipated, the non-linear deep learning strategies outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are an alternative payment methodology which will replace intermediaries with cryptographic strategies and must be embedded within the research areas of SIGeBIZ and SIGSEC. In this paper we suggest to treatment this drawback through the use of the methods initially developed for the pc-aided evaluation for hardware and software program techniques, particularly those primarily based on the timed automata. In this paper we introduce a instrument [https://uchatoo.com/post/123406_https-www-analyticsinsight-net-where-to-buy-bitcoin-2022-defending-the-privacy-o.html where to buy bitcoin] study and analyze the UTXO set, along with an in depth description of the set format and performance. This paper provides an evaluation of the current state of the literature. This systematic literature assessment examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know all the pieces you need [https://yogicentral.science/wiki/We_Investigate_The_Risk_Of_Bitcoin where to buy bitcoin] have the ability to separate fact from fiction when reading claims about Bitcoin and other cryptocurrencies. We show the time-various contribution ui(t) of the first six base networks on determine 2. In most cases, ui(t) features a couple of abrupt changes, partitioning the historical past of Bitcoin into separate time durations. In the initial phase is high, fluctuating around (see Fig. 5), probably a result of transactions taking place between addresses belonging to a couple lovers trying out the Bitcoin system by shifting money between their own addresses.
|
Horodatage Unix de la modification (timestamp) | 1647766562 |