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NEW QUESTION: 1
What happens when you attempt to compile and run the following code?
#include <iostream>
#include <algorithm>
#include <vector>
using namespace std;
int main () {
int t[] = {1,2,3,4,5,1,2,3,5,4};
vector<int> v (t,t+10);
vector<int>::iterator it;
int m1[] = {1, 3, 2};
it = find_end (v.begin(), v.end(), m1, m1+3);
if (it != v.end())
cout << "Found at position: " << it?v.begin() << endl;
return 0;
}
A. program outputs: Found at position: 5
B. program outputs: Found at position: 10
C. program outputs: Found at position: 0
D. no output
Answer: D

NEW QUESTION: 2
Refer to the exhibit.

You notice this error message in the syslog. Which command do you enter on the switch to gather more information?
A. Show ip arp
B. Show ip source binding
C. Show ip dhcp snooping binding
D. Show mac address-table
Answer: C

NEW QUESTION: 3
You are developing a Windows Presentation Foundation (WPF) application.
You configure PresentationTraceSource to track errors in a bound TextBox control in the application.
You need to choose the window that the Trace Information is sent to.
Which Visual Studio window should you select?
A. Autos
B. Locals
C. Output
D. Immediate
Answer: C

NEW QUESTION: 4
Overview:
Litware, Inc. is a company that manufactures personal devices to track physical activity and other health- related data.
Litware has a health tracking application that sends health-related data from a user's personal device to Microsoft Azure.
Litware has three development and commercial offices. The offices are located in the United States, Luxembourg, and India.
Litware products are sold worldwide. Litware has commercial representatives in more than 80 countries.
Existing Environment:
In addition to using desktop computers in all of the offices, Litware recently started using Microsoft Azure resources and services for both development and operations.
Litware has an Azure Machine Learning solution.
Litware recently extended its platform to provide third-party companies with the ability to upload data from devices to Azure. The data can be aggregated across multiple devices to provide users with a comprehensive view of their global health activity.
While the upload from each device is small, potentially more than 100 million devices will upload data daily by using an Azure event hub.
Each health activity has a small amount of data, such as activity type, start date/time, and end date/time.
Each activity is limited to a total of 3 KB and includes a customer identification key.
In addition to the Litware health tracking application, the users' activities can be reported to Azure by using an open API.
The developers at Litware perform Machine Learning experiments to recommend an appropriate health activity based on the past three activities of a user.
The Litware developers train a model to recommend the best activity for a user based on the hour of the day.
Requirements:
Litware plans to extend the existing dashboard features so that health activities can be compared between the users based on age, gender, and geographic region.
Minimize the costs associated with transferring data from the event hub to Azure Storage.
Litware identifies the following technical requirements:
Data from the devices must be stored for three years in a format that enables the fast processing of

date fields and filtering.
The third-party companies must be able to use the Litware Machine Learning models to generate

recommendations to their users by using a third-party application.
Any changes to the health tracking application must ensure that the Litware developers can run the

experiments without interrupting or degrading the performance of the production environment.
Activity tracking data must be available to all of the Litware developers for experimentation. The developers must be prevented from accessing the private information of the users.
When the Litware health tracking application asks users how they feel, their responses must be reported to Azure.
Users report that when they access data that is more than one year old from a dashboard, the response time is slow.
You need to resolve the issue that causes the slow response when visualizing older data.
What should you do?
A. Process the older data on demand first, and then process the event hub data.
B. Process the event hub data first, and then process the older data on demand.
C. Aggregate the older data by time, and then save the aggregated data to reference data streams.
D. Store all of the data from the event hub in a single partition.
Answer: C
Explanation:
Explanation/Reference:
Explanation: