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NEW QUESTION: 1
When the nurse is caring for a patient placed on droplet precautions, the nurse should:
A. Apply a disposable gown when entering the patient's room
B. Wear a surgical mask when standing within 3 feet (1 meter) of the patient
C. Have the patient wear a high-efficiency particulate air (HEPA) mask
D. Assign the patient to a room with monitored negative air pressure
Answer: B

NEW QUESTION: 2
DHCPが使用するポートは次のうちどれですか？ （2つ選択）。
A. 0
B. 1
C. 2
D. 3
E. 4
Answer: A,C

NEW QUESTION: 3
Your company has two offices. The offices are located in London and New York.
The London office has a public IP of 131.107.1.1 and a private IP subnet of 192.168.4.0/24. The New York office has a public IP of 131.107.15.1 and a private IP subnet of 192.168.8.0/24.
You have a Microsoft SQL Server database that is hosted on a Microsoft Azure virtual machine. Currently, only the users in the London office use the database.
You need to create a new firewall rule to provide the users in the New York office with access to the database.
The solution must protect the database from being accessed by users on the public Internet.
What should you do?
A. Run the New-AzureSqlDatabaseServerFirewallRule Azure PowerShell cmdlet.
B. Disable the Windows Firewall on the Azure virtual machine.
C. Modify the endpoint from the Azure portal.
D. Use the sp_set_database_firewall_rule stored procedure.
E. Use the Set Firewall Rule REST API.
Answer: C
Explanation:
Explanation
This Microsoft SQL Server database is hosted on a Microsoft Azure virtual machine. Therefore, remote access will be provided via the endpoint rather than a database level firewall rule.

NEW QUESTION: 4
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure ML experiment that contains an intermediate dataset.
You need to explore data from the intermediate dataset by using Jupyter.
Solution: You add a Convert to CSV module to the Azure ML experiment and then open the module output in a new notebook.
Does this meet the goal?
A. No
B. Yes
Answer: B
Explanation:
Explanation/Reference:
Explanation:
Access intermediate datasets from Machine Learning experiments
The following steps show an example that creates an experiment, runs it and accesses the intermediate dataset.
1. Create a new experiment.
2. Insert an Adult Census Income Binary Classification dataset module.
3. Insert a Split module, and connect its input to the dataset module output.
4. Insert a Convert to CSV module and connect its input to one of the Split module outputs.
5. Save the experiment, run it, and wait for it to finish running.
6. Click the output node on the Convert to CSV module.
7. When the context menu appears, select Generate Data Access Code
8. Select the code snippet and copy it to your clipboard from the window that appears..
9. Paste the code in your notebook.
Note: After an experiment is run in the Machine Learning Studio, it is possible to access the intermediate datasets from the output nodes of modules. Intermediate datasets are data that has been created and used for intermediate steps when a model tool has been run.
Intermediate datasets can be accessed as long as the data format is compatible with the Python client library.
The following formats are supported (constants for these are in the azureml.DataTypeIds class):
PlainText

GenericCSV

GenericTSV

GenericCSVNoHeader

GenericTSVNoHeader

References: https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/python- data-access