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) | AdrianQ97660 |
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) | AdrianQ97660 |
Titre complet de la page (article_prefixedtext) | Utilisateur:AdrianQ97660 |
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 methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another payment methodology that will exchange intermediaries with cryptographic methods and needs to be embedded within the research areas of SIGeBIZ and SIGSEC. On this paper we suggest to remedy this drawback by using the methods originally developed for the computer-aided analysis for hardware and software systems, particularly those primarily based on the timed automata. In this paper we introduce a software to check and analyze the UTXO set, along with an in depth description of the set format and performance. This paper gives an assessment of the present state of the literature. This systematic literature review examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know everything you want to have the ability to separate truth from fiction when reading claims about Bitcoin and other cryptocurrencies. We present the time-varying contribution ui(t) of the primary six base networks on figure 2. Generally, ui(t) options a number of abrupt modifications, partitioning the historical past of Bitcoin into separate time intervals. Within the initial phase is high, fluctuating round (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>Feel free to visit my blog post [http://www.mrleffsclass.com/forum/member.php?action=profile&uid=613970 lucky block] |
Diff unifié des changements faits lors de la modification (edit_diff) | @@ -1,1 +1,1 @@
-
+As expected, the non-linear deep learning methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another payment methodology that will exchange intermediaries with cryptographic methods and needs to be embedded within the research areas of SIGeBIZ and SIGSEC. On this paper we suggest to remedy this drawback by using the methods originally developed for the computer-aided analysis for hardware and software systems, particularly those primarily based on the timed automata. In this paper we introduce a software to check and analyze the UTXO set, along with an in depth description of the set format and performance. This paper gives an assessment of the present state of the literature. This systematic literature review examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know everything you want to have the ability to separate truth from fiction when reading claims about Bitcoin and other cryptocurrencies. We present the time-varying contribution ui(t) of the primary six base networks on figure 2. Generally, ui(t) options a number of abrupt modifications, partitioning the historical past of Bitcoin into separate time intervals. Within the initial phase is high, fluctuating round (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>Feel free to visit my blog post [http://www.mrleffsclass.com/forum/member.php?action=profile&uid=613970 lucky block]
|
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 that will exchange intermediaries with cryptographic methods and needs to be embedded within the research areas of SIGeBIZ and SIGSEC. On this paper we suggest to remedy this drawback by using the methods originally developed for the computer-aided analysis for hardware and software systems, particularly those primarily based on the timed automata. In this paper we introduce a software to check and analyze the UTXO set, along with an in depth description of the set format and performance. This paper gives an assessment of the present state of the literature. This systematic literature review examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know everything you want to have the ability to separate truth from fiction when reading claims about Bitcoin and other cryptocurrencies. We present the time-varying contribution ui(t) of the primary six base networks on figure 2. Generally, ui(t) options a number of abrupt modifications, partitioning the historical past of Bitcoin into separate time intervals. Within the initial phase is high, fluctuating round (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>Feel free to visit my blog post [http://www.mrleffsclass.com/forum/member.php?action=profile&uid=613970 lucky block]
|
Horodatage Unix de la modification (timestamp) | 1650692316 |
