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 expected, the non-linear deep learning strategies outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another payment technique that will replace intermediaries with cryptographic methods and must be embedded within the analysis areas of SIGeBIZ and SIGSEC. On this paper we suggest to remedy this downside through the use of the strategies initially developed for the pc-aided analysis for hardware and software programs, in particular those primarily based on the timed automata. On this paper we introduce a software [https://www.estekhdamiranian.ir/author/sparkpower12/ where to buy bitcoin] 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 present state of the literature. This systematic literature assessment examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know every little thing you need to have the ability to separate truth from fiction when studying claims about Bitcoin and other cryptocurrencies. We present the time-varying contribution ui(t) of the first six base networks on figure 2. Normally, ui(t) options just a few abrupt adjustments, partitioning the history of Bitcoin into separate time durations. Within the initial section is high, fluctuating round (see Fig. 5), presumably a results of transactions going down between addresses belonging to a few lovers trying out the Bitcoin system by shifting cash between their very own addresses. |
Diff unifié des changements faits lors de la modification (edit_diff) | @@ -1,1 +1,1 @@
-%About_Yourself%
+As expected, the non-linear deep learning strategies outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another payment technique that will replace intermediaries with cryptographic methods and must be embedded within the analysis areas of SIGeBIZ and SIGSEC. On this paper we suggest to remedy this downside through the use of the strategies initially developed for the pc-aided analysis for hardware and software programs, in particular those primarily based on the timed automata. On this paper we introduce a software [https://www.estekhdamiranian.ir/author/sparkpower12/ where to buy bitcoin] 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 present state of the literature. This systematic literature assessment examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know every little thing you need to have the ability to separate truth from fiction when studying claims about Bitcoin and other cryptocurrencies. We present the time-varying contribution ui(t) of the first six base networks on figure 2. Normally, ui(t) options just a few abrupt adjustments, partitioning the history of Bitcoin into separate time durations. Within the initial section is high, fluctuating round (see Fig. 5), presumably a results of transactions going down between addresses belonging to a few lovers trying out the Bitcoin system by shifting cash between their very own addresses.
|
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 another payment technique that will replace intermediaries with cryptographic methods and must be embedded within the analysis areas of SIGeBIZ and SIGSEC. On this paper we suggest to remedy this downside through the use of the strategies initially developed for the pc-aided analysis for hardware and software programs, in particular those primarily based on the timed automata. On this paper we introduce a software [https://www.estekhdamiranian.ir/author/sparkpower12/ where to buy bitcoin] 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 present state of the literature. This systematic literature assessment examines cryptocurrencies (CCs) and Bitcoin. After this course, you’ll know every little thing you need to have the ability to separate truth from fiction when studying claims about Bitcoin and other cryptocurrencies. We present the time-varying contribution ui(t) of the first six base networks on figure 2. Normally, ui(t) options just a few abrupt adjustments, partitioning the history of Bitcoin into separate time durations. Within the initial section is high, fluctuating round (see Fig. 5), presumably a results of transactions going down between addresses belonging to a few lovers trying out the Bitcoin system by shifting cash between their very own addresses.
|
Horodatage Unix de la modification (timestamp) | 1647715931 |
