You have a Class C network. You want to subnet it such that you have at least 5 hosts per subnet. How many subnets can you have?

You have a Class C network. You want to subnet it such that you have at least 25 hosts per subnet. How many subnets can you have?

Which command will take your machine back to a "blank" state? It will not know its own name/IP or any other machines in the network ?

Your have a class C network. The IP addresses of your workstations start with 128.251.143 . What is the network address of your network ?

Your have a class C network. The IP addresses of your workstations start with 128.251.143 . What is the broadcast address of your network?

Our company order a cisco ws-c3750x-48t-s(here i bought from http://www.3anetwork.com/cisco-ws-c3750x-48t-s-price_p104.html), As for the switch, in addition to the port module and optical module can be extended, what else module can also be extended?

Aptron,

how to calculate the mesh earth network resistance in such substation, is there any recommended resistance values with references , thanks!

SRES,

 What does the Bayesian network provides? a) Complete description of the domain b) Partial description of the domain c) Complete description of the problem d) None of the mentioned

 What is the consequence between a node and its predecessors while creating Bayesian network? a) Conditionally dependent b) Dependent c) Conditionally independent d) Both a & b

An auto-associative network is: a) a neural network that contains no loops b) a neural network that contains feedback c) a neural network that has only one loop d) a single layer feed-forward neural network with pre-processing

 Which of the following is true for neural networks? (i) The training time depends on the size of the network. (ii) Neural networks can be simulated on a conventional computer. (iii) Artificial neurons are identical in operation to biological ones. a) All of the mentioned b) (ii) is true c) (i) and (ii) are true d) None of the mentioned

 What are the advantages of neural networks over conventional computers? (i) They have the ability to learn by example (ii) They are more fault tolerant (iii)They are more suited for real time operation due to their high ‘computational’ rates a) (i) and (ii) are true b) (i) and (iii) are true c) Only (i) d) All of the mentioned

Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned

Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex binary operation that cannot be solved using neural networks c) Because it can be solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

. Why are linearly separable problems of interest of neural network researchers? a) Because they are the only class of problem that network can solve successfully b) Because they are the only class of problem that Perceptron can solve successfully c) Because they are the only mathematical functions that are continue d) Because they are the only mathematical functions you can draw