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NEW QUESTION: 1
얼굴 인식 소프트웨어를 사용하는 생체 인식 시스템을 선택하고 배포하기 전에 다음 중 완료해야 하는 것은 무엇입니까?
A. 취약성 평가
B. 개인 정보 영향 분석가
C. 이미지 간섭 검토
D. 허위 수용 테스트
Answer: D

NEW QUESTION: 2



Log started
Base: Log continuing
Finished


Answer:
Explanation:

Explanation
Box 1:

Box 2:

Box 3:

Box 4:

Incorrect:
Not Box 4: logger.LogCompleted();
The output would incorrectly be "Completed"

NEW QUESTION: 3
ESX Server uses_____________ locks, which are managed by the VMFS distributed lock manager.
A. disk level
B. drive level
C. file level
D. vmfs level
Answer: C
Explanation:
VMFS CAN Coordinate access to virtual disk files . ESX Server uses file level locks, which are managed by the VMFS distributed lock manager.

NEW QUESTION: 4
デバイスが指定された場所から200メートル以上移動したときにユーザーに警告するリアルタイム監視アプリを作成する予定です。
計画したアプリのデータを処理するには、Azure Stream Analyticsジョブを設計する必要があります。 このソリューションでは、開発するコードの量と使用するテクノロジーの数を最小限に抑える必要があります。
Stream Analyticsジョブには何を含め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:
Input type: Stream
You can process real-time IoT data streams with Azure Stream Analytics.
Input source: Azure IoT Hub
In a real-world scenario, you could have hundreds of these sensors generating events as a stream. Ideally, a gateway device would run code to push these events to Azure Event Hubs or Azure IoT Hubs.
Function: Geospatial
With built-in geospatial functions, you can use Azure Stream Analytics to build applications for scenarios such as fleet management, ride sharing, connected cars, and asset tracking.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-get-started-with-azure-stream-analytics-to-process-data-from-iot-devices
https://docs.microsoft.com/en-us/azure/stream-analytics/geospatial-scenarios