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 another cost technique that may replace intermediaries with cryptographic methods and ought to be embedded in the research areas of SIGeBIZ and SIGSEC. In this paper we suggest to treatment this drawback by using the strategies originally developed for the computer-aided analysis for hardware and software programs, particularly those based mostly on the timed automata. On this paper we introduce a software [http://www.maikefx.com/home.php?mod=space&uid=118379 where to buy bitcoin] review and analyze the UTXO set, together with a detailed description of the set format and performance. This paper provides an assessment of the current state of the literature. This systematic literature evaluate examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know all the pieces you need [http://occtao.com/index.php?qa=user&qa_1=bikefelony25 where to buy bitcoin] be able to separate reality from fiction when reading claims about Bitcoin and different cryptocurrencies. We show the time-various contribution ui(t) of the first six base networks on figure 2. Normally, ui(t) features just a few abrupt changes, partitioning the history of Bitcoin into separate time durations. Within the initial section is excessive, fluctuating round (see Fig. 5), probably a result of transactions happening between addresses belonging to a couple lovers making an attempt out the Bitcoin system by transferring 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 methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another cost technique that may replace intermediaries with cryptographic methods and ought to be embedded in the research areas of SIGeBIZ and SIGSEC. In this paper we suggest to treatment this drawback by using the strategies originally developed for the computer-aided analysis for hardware and software programs, particularly those based mostly on the timed automata. On this paper we introduce a software [http://www.maikefx.com/home.php?mod=space&uid=118379 where to buy bitcoin] review and analyze the UTXO set, together with a detailed description of the set format and performance. This paper provides an assessment of the current state of the literature. This systematic literature evaluate examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know all the pieces you need [http://occtao.com/index.php?qa=user&qa_1=bikefelony25 where to buy bitcoin] be able to separate reality from fiction when reading claims about Bitcoin and different cryptocurrencies. We show the time-various contribution ui(t) of the first six base networks on figure 2. Normally, ui(t) features just a few abrupt changes, partitioning the history of Bitcoin into separate time durations. Within the initial section is excessive, fluctuating round (see Fig. 5), probably a result of transactions happening between addresses belonging to a couple lovers making an attempt out the Bitcoin system by transferring money between their own addresses.
|
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 another cost technique that may replace intermediaries with cryptographic methods and ought to be embedded in the research areas of SIGeBIZ and SIGSEC. In this paper we suggest to treatment this drawback by using the strategies originally developed for the computer-aided analysis for hardware and software programs, particularly those based mostly on the timed automata. On this paper we introduce a software [http://www.maikefx.com/home.php?mod=space&uid=118379 where to buy bitcoin] review and analyze the UTXO set, together with a detailed description of the set format and performance. This paper provides an assessment of the current state of the literature. This systematic literature evaluate examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know all the pieces you need [http://occtao.com/index.php?qa=user&qa_1=bikefelony25 where to buy bitcoin] be able to separate reality from fiction when reading claims about Bitcoin and different cryptocurrencies. We show the time-various contribution ui(t) of the first six base networks on figure 2. Normally, ui(t) features just a few abrupt changes, partitioning the history of Bitcoin into separate time durations. Within the initial section is excessive, fluctuating round (see Fig. 5), probably a result of transactions happening between addresses belonging to a couple lovers making an attempt out the Bitcoin system by transferring money between their own addresses.
|
Horodatage Unix de la modification (timestamp) | 1647772570 |
