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NEW QUESTION: 1
The Oracle Applications Release 12 processes on the application tier are started successfully. The Applications database administrator (DBA) must apply a patch while the users are still using Oracle Applications.
According to the instructions from readme.txt of the patch to be applied, only the concurrent manager process must be shut down before applying the patch. After the patch is applied successfully, one should start the concurrent manager processes.
The Applications DBA performs these steps to apply the patch on the application tier:
Step 1: Logs in to the application tier as "applmgr"
Step 2: Changes to the $INST_TOP/admin/scripts directory
Step 3: Executes the adstpall.sh script
Step 4: Applies the patch
Step 5: Checks the log file of the patch for any errors
Step 6: Runs the $INST_TOP/admin/scripts/adstrtal.sh script
What do you conclude?
A. In the third step, the adstpall.sh script should not be used.
B. In the first step, the user should be oracle instead of applmgr.
C. In the sixth step, the location of the script is wrong.
D. There are no mistakes in the steps.
Answer: A

NEW QUESTION: 2
A company needs to ingest terabytes of data each hour from thousands of sources that are delivered almost continually throughout the day. The volume of messages generated varies over the course of the day.
Messages must be delivered in real time for fraud detection and live operational dashboards.
Which approach will meet these requirements?
A. Send the messages to an Amazon SQS queue, then process the messages by using a fleet of Amazon EC2 instances
B. Use the Amazon S3 API to write messages to an S3 bucket, then process the messages by using Amazon Redshift
C. Use AWS Data Pipeline to automate the movement and transformation of data
D. Use Amazon Kinesis Data Streams with Kinesis Client Library to ingest and deliver messages
Answer: D

NEW QUESTION: 3
Tony has created the following categories within IBM Web Content Manager: Article > Practice Management > Tech Article > Practice Management > Finance He now wants to create a menu that returns results for all content items that use the News authoring template and all Categories under Article > Practice Management. Which of the following examples would allow him to accomplish this task?
A. 1. In Menu Criteria, Tony selects the Authoring Templates and Categories check boxes.
2.In the Authoring Templates section, Tony clicks the Add Authoring Template button and selects
the News authoring template.
3.In the Categories section, Tony clicks the Include ancestors check box and then clicks the Add
Categories section and selects Article >
Practice Management > Tech and Article > Practice Management > Finance.
B. 1. In Menu Criteria, Tony selects the Authoring Templates and Categories check boxes.
2.In the Authoring Templates section, Tony clicks the Add Authoring Template button and selects
the News authoring template.
3.In the Categories section, Tony clicks the Include ancestors check box and then clicks the Add
Categories section and selects Article >
Practice Management.
C. 1. In Menu Criteria, Tony selects the Authoring Templates and Categories check boxes.
2.In the Authoring Templates section, Tony clicks the Add Authoring Template button and selects
the News authoring template.
3.In the Categories section, Tony clicks the Include descendents check box and then clicks the
Add Categories section and selects Article >
Practice Management.
D. 1. In Menu Criteria, Tony selects the Authoring Templates and Categories check boxes.
2.In the Authoring Templates section, Tony clicks the Add Authoring Template button and selects
the News authoring template.
3.In the "Categories" section, Tony clicks the Results must match all categories check box and
then clicks the Add Categories section andselects Article > Practice Management > Tech and
Article > Practice Management > Finance.
Answer: C

NEW QUESTION: 4
特徴抽出方法を選択する必要があります。
どの方法を使用する必要がありますか？
A. ケンドール相関
B. 相互情報
C. ムードの中央値検定
D. 順列機能の重要性
Answer: A
Explanation:
In statistics, the Kendall rank correlation coefficient, commonly referred to as Kendall's tau coefficient (after the Greek letter t), is a statistic used to measure the ordinal association between two measured quantities.
It is a supported method of the Azure Machine Learning Feature selection.
Scenario: When you train a Linear Regression module using a property dataset that shows data for property prices for a large city, you need to determine the best features to use in a model. You can choose standard metrics provided to measure performance before and after the feature importance process completes. You must ensure that the distribution of the features across multiple training models is consistent.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/feature-selection-modules