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NEW QUESTION: 1
Click on the Exhibit button.
Which statement is true about the availability of the system shown in the diagram?
A. The system is highly available because redundant application servers are provided.
B. The system is not highly available because no redundant storage is provided.
C. The system is highly available because multiple content servers are provided.
D. The system is not highly available because only a single content server serves each repository.
Answer: D
NEW QUESTION: 2
A network's design includes gateways connecting an assembly-line network. The assembly-line network users specialized cabling and interfaces to allow the assembly-line robots to communicate with one another. The IP is connecting the technician workstations with which of the following network types?
A. LAN
B. CSU/DSU
C. IS-IS
D. SCADA/ICS
Answer: D
Explanation:
Explanation
https://en.wikipedia.org/wiki/SCADA
NEW QUESTION: 3
Refer to the exhibit.
The two exhibited devices are the only Cisco devices on the network. The serial network between the two devices has a mask of 255.255.255.252. Given the output that is shown, what three statements are true of these devices? (Choose three.)
A. The London router is a Cisco 2610.
B. The CDP information was sent by port Serial0/0 of the London router.
C. The Manchester serial address is 10.1.1.2.
D. The Manchester router is a Cisco 2610.
E. The CDP information was received on port Serial0/0 of the Manchester router.
F. The Manchester serial address is 10.1.1.1.
Answer: A,E,F
Explanation:
Explanation/Reference:
Explanation:
NEW QUESTION: 4
Business owners at your company have given you a database of bank transactions. Each row contains the
user ID, transaction type, transaction location, and transaction amount. They ask you to investigate what
type of machine learning can be applied to the data. Which three machine learning applications can you
use? (Choose three.)
A. Reinforcement learning to predict the location of a transaction.
B. Unsupervised learning to predict the location of a transaction.
C. Supervised learning to determine which transactions are most likely to be fraudulent.
D. Unsupervised learning to determine which transactions are most likely to be fraudulent.
E. Supervised learning to predict the location of a transaction.
F. Clustering to divide the transactions into N categories based on feature similarity.
Answer: A,D,F