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NEW QUESTION: 1
セキュリティ管理者が、ネットワークスイッチとルーターに2要素認証を実装したいと考えています。このソリューションは、ネットワークインフラストラクチャデバイスの認証に使用される会社のRADIUSサーバーと統合する必要があります。セキュリティ管理者は以下を実装します。
* RADIUSサーバーにHOTPサービスがインストールされています。
* RADIUSサーバーは認証にHOTPサービスを要求するように設定されています。
設定はソフトウェアサプリカントを使用して正常にテストされ、すべてのネットワークデバイスに適用されます。ネットワーク管理者は、2番目の要素の入力を求められていないため、ネットワークデバイスにログオンできないと報告しています。
次のうちどれが問題を最もよく解決するために実行されるべきですか。
A. パスワードに追加された2番目の要素を受け入れるようにRADIUSサーバーを設定します。
ネットワーク管理者はパスワードフィールドにパスワードを入力し、その後にトークンを入力します。
B. ユーザー名、パスワード、およびトークンを要求するようにネットワークデバイスを再設定します。ネットワーク管理者は自分のユーザー名とパスワードを入力してから、トークンを入力します。
C. パスワード要件を2番目の要素に置き換えます。ネットワーク管理者は自分のユーザー名を入力してから、パスワードフィールドに自分のパスワードの代わりにトークンを入力します。
D. HOTPサービスに加えて、TOTPサービスをRADIUSサーバーにインストールします。 2要素認証をサポートしていない古いデバイスではHOTPを使用してください。ネットワーク管理者はこれらのデバイスにログオンするためにWebポータルを使用します。
Answer: A

NEW QUESTION: 2
You have a multi-class image classification deep learning model that uses a set of labeled photographs. You create the following code to select hyperparameter values when training the model.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: Yes
Hyperparameters are adjustable parameters you choose to train a model that govern the training process itself. Azure Machine Learning allows you to automate hyperparameter exploration in an efficient manner, saving you significant time and resources. You specify the range of hyperparameter values and a maximum number of training runs. The system then automatically launches multiple simultaneous runs with different parameter configurations and finds the configuration that results in the best performance, measured by the metric you choose. Poorly performing training runs are automatically early terminated, reducing wastage of compute resources. These resources are instead used to explore other hyperparameter configurations.
Box 2: Yes
uniform(low, high) - Returns a value uniformly distributed between low and high Box 3: No Bayesian sampling does not currently support any early termination policy.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters

NEW QUESTION: 3
Which two are true? (Choose two.)
A. Classes in the java.awt package are designed to provide lightweight components that work the same across different platforms.
B. Classes in the javax.swing package provide support for complex GUI components, such as tables and trees.
C. Classes in the java.awt package inherit many behaviors from classes in the java.swing package.
D. Classes in the java.awt package are used to paint objects on canvases.
Answer: B,D