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NEW QUESTION: 1
You have a Microsoft Exchange Server 2019 hybrid deployment.
All Mailbox servers and domain controllers are in the same site.
You deploy an Edge Transport server.
You need to ensure that all SMTP traffic between the on-premises organization and Exchange Online is routed through the Edge Transport server.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation
New-EdgeSubscription -FileName "c:\EdgeServerSubscription.xml" This example creates the Edge Subscription file. It should be run on your Edge Transport server. New-EdgeSubscription -FileData ([byte[]]$(Get-Content -Path "C:\EdgeServerSubscription.xml" -Encoding Byte -ReadCount 0)) -Site
"Default-First-Site-Name" This example also imports the Edge Subscription file generated in Example 1 to the Active Directory site Default-First-Site-Name; however, the end result is accomplished using one command.
You must run this command on the Mailbox server. ref.
https://docs.microsoft.com/en-us/powershell/module/exchange/mail-flow/new-edgesubscription?view=exchange
NEW QUESTION: 2
A. 10.10.0.0/18 subnetted with mask 255.255.255.252
B. 10.10.0.0/23 subnetted with mask 255.255.255.252
C. 10.10.1.0/24 subnetted with mask 255.255.255.252
D. 10.10.1.0/25 subnetted with mask 255.255.255.252
E. 10.10.0.0/16 subnetted with mask 255.255.255.252
Answer: B
Explanation:
Explanation
We need 113 point-to-point links which equal to 113 sub-networks < 128 so we need to borrow 7
bits (because 2
NEW QUESTION: 3
Which of the following technologies can help optimize capacity utilization when storing many versions of a large file with few changes in each revision of the file?
A. Block-level deduplication
B. Asynchronous replication
C. Single instance storage
D. File-level deduplication
Answer: A
NEW QUESTION: 4
Match the types of computer vision to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Facial recognition
Face detection that perceives faces and attributes in an image; person identification that matches an individual in your private repository of up to 1 million people; perceived emotion recognition that detects a range of facial expressions like happiness, contempt, neutrality, and fear; and recognition and grouping of similar faces in images.
Box 2: OCR
Box 3: Objection detection
Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can use this functionality to process the relationships between the objects in an image. It also lets you determine whether there are multiple instances of the same tag in an image.
The Detect API applies tags based on the objects or living things identified in the image. There is currently no formal relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the Detect API only finds objects and living things, while the Tag API can also include contextual terms like "indoor", which can't be localized with bounding boxes.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/face/
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection
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