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NEW QUESTION: 1
Mit welcher der folgenden Methoden kann der Urheber einer Transaktion effektiv überprüft werden?
A. Verwenden eines geheimen Passworts zwischen dem Absender und dem Empfänger
B. Die Transaktion wird mit dem öffentlichen Schlüssel des Empfängers verschlüsselt
C. Verwenden eines PDF-Formats (Portable Document Format) zum Einkapseln von Transaktionsinhalten
D. Digitale Signatur der Transaktion mit dem privaten Schlüssel der Quelle
Answer: D
Explanation:
Erläuterung:
Eine digitale Signatur ist eine elektronische Identifikation einer Person, die unter Verwendung eines Algorithmus mit öffentlichem Schlüssel erstellt wurde, um einem Empfänger die Identität der Quelle einer Transaktion und die Integrität ihres Inhalts zu bestätigen. Da sie ein "gemeinsames Geheimnis" zwischen dem Benutzer und dem System selbst sind, werden Kennwörter als schwächeres Mittel zur Authentifizierung angesehen. Durch das Verschlüsseln der Transaktion mit dem öffentlichen Schlüssel des Empfängers werden die Informationen vertraulich behandelt, während durch die Verwendung eines PDF-Formats (Portable Document Format) die Integrität des Inhalts geprüft wird, jedoch nicht unbedingt die Urheberschaft.

NEW QUESTION: 2
Refer to the exhibit. Which statement about the authentication protocol used in the configuration is the ...? aaa new model Radius-server host 10.0.0.12 key secret12
A. The authentication request contains only a password On RADIUS, authentication & authorization are grouped in single packet, not like TACACS+ who separated them
B. The authentication request contains only a username
C. There is separate authentication and authorization request packet.
D. The authentication and authorization requests are grouped in single packets.
Answer: D

NEW QUESTION: 3
注：この質問は、同じシナリオを提示する一連の質問の一部です。シリーズの各質問には、記載された目標を達成する可能性のある独自のソリューションが含まれています。一部の質問セットには複数の正しい解決策がある場合もあれば、正しい解決策がない場合もあります。
このセクションの質問に回答すると、その質問に戻ることはできません。その結果、これらの質問はレビュー画面に表示されません。
複数の列に欠損値を含む数値データセットを分析しています。
機能セットの次元に影響を与えることなく、適切な操作を使用して欠損値を消去する必要があります。
すべての値を含めるには、完全なデータセットを分析する必要があります。
解決策：連鎖方程式による多重代入（MICE）メソッドを使用して、各欠損値を置き換えます。
ソリューションは目標を達成していますか？
A. はい
B. いいえ
Answer: A
Explanation:
Explanation
Replace using MICE: For each missing value, this option assigns a new value, which is calculated by using a method described in the statistical literature as "Multivariate Imputation using Chained Equations" or
"Multiple Imputation by Chained Equations". With a multiple imputation method, each variable with missing data is modeled conditionally using the other variables in the data before filling in the missing values.
Note: Multivariate imputation by chained equations (MICE), sometimes called "fully conditional specification" or "sequential regression multiple imputation" has emerged in the statistical literature as one principled method of addressing missing data. Creating multiple imputations, as opposed to single imputations, accounts for the statistical uncertainty in the imputations. In addition, the chained equations approach is very flexible and can handle variables of varying types (e.g., continuous or binary) as well as complexities such as bounds or survey skip patterns.
References:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3074241/
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data

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