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NEW QUESTION: 1
A woman is most likely to get pregnant if she has unprotected sex a few days before and on the day of ovulation, when the egg is released from the ovaries. The release of the egg is hormonally stimulated, meaning that a hormone in the woman's body triggers ovulation. On average, women ovulate around the
14th day of their menstrual cycle. The following is a graph showing the levels of three hormones throughout the menstrual cycle of an average woman.
Based on the graph, which hormone is most directly responsible for triggering ovulation?
A. cholesterol
B. testosterone
C. progesterone
D. LH
E. FSH
Answer: D
Explanation:
Explanation/Reference:
Explanation:
The graph shows that the level of LH rapidly rises right before the 14th day of the cycle, and then falls.
NEW QUESTION: 2
企業は、バケットにアップロードされたオブジェクトが暗号化されていることを確認する必要があります。次のアクションのどれがこの要件を満たしますか？ （2を選択）
A. 暗号化されていないオブジェクトがS3バケットにアップロードされるのを拒否するために、オブジェクトアクセス制御リスト（ACL）を実装します。
B. Amazon S3のデフォルトの暗号化を実装して、アップロードされるオブジェクトが保存される前に必ず暗号化されるようにします。
C. S3バケットに格納されている暗号化されていないオブジェクトから保護するためにAWS Shieldを実装します
D. Amazon Inspectorを実装して、S3にアップロードされたオブジェクトを検査します。それらが暗号化されていることを確認します。
E. 暗号化されていないオブジェクトがバケットにアップロードされるのを拒否するS3バケットポリシーを実装します。
Answer: A,B
Explanation:
デフォルトでは、すべてのS3バケットはプライベートであり、明示的にアクセスが許可されているユーザーのみがアクセスできます。ほとんどのユースケースでは、S3を使用してパブリックアセットをホストする（たとえば、パブリックWebサイトで使用するためのイメージをホストする）場合を除き、S3バケットからファイルを読み取るための広範なパブリックアクセスは必要ありません。決して一般に開放されていることバケットACLとIAMおよびバケットポリシーの組み合わせを使用して、S3リソースへのアクセスを制御できます。 AWSは、サーバーアクセスログ、Amazon CloudWatchログ、AWS CloudTrail、AWS Trusted Advisorなど、セキュリティ設定の監視と監査に役立つサービスも提供しています。
NEW QUESTION: 3
Azure Machine Learning Studioで分類タスクを実行しています。
提供されたデータセットに基づいて、バランスの取れたテストおよびトレーニングサンプルを準備する必要があります。
0.75：0.25の比率でデータを分割する必要があります。
各パラメーターにどの値を使用する必要がありますか？ 回答するには、回答エリアで適切なオプションを選択します。
注：それぞれの正しい選択には1ポイントの価値があります。
Answer:
Explanation:
Explanation:
Box 1: Split rows
Use the Split Rows option if you just want to divide the data into two parts. You can specify the percentage of data to put in each split, but by default, the data is divided 50-50.
You can also randomize the selection of rows in each group, and use stratified sampling. In stratified sampling, you must select a single column of data for which you want values to be apportioned equally among the two result datasets.
Box 2: 0.75
If you specify a number as a percentage, or if you use a string that contains the "%" character, the value is interpreted as a percentage. All percentage values must be within the range (0, 100), not including the values 0 and 100.
Box 3: Yes
To ensure splits are balanced.
Box 4: No
If you use the option for a stratified split, the output datasets can be further divided by subgroups, by selecting a strata column.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/split-data
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