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Define Cloud Computing with example.
Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., servers, networks, storage, applications, and services) that can be quickly provisioned and released with minimal management effort or service provider interaction. For instance, Google hosts a cloud that having of both smallish PCs and larger servers.
Q. Components of magnetic disk? Disk itself is mounted in a disk drive that comprises arm which is a shaft that rotates disk and the electronics required for input and output b
What is the function of a TLB (translation look-aside buffer)? A small cache called the TLB is interporated into MMU, which having of the page table entries that correspondi
Massively Parallel System Refers to a parallel computer system having a great number of processors. The number in a great number of keeps increasing and currently it means more
Implement the following function using 8 to 1 multiplexer Y(A, B, C, D) = ∑(0,1,2,5,9,11,13,15) Ans. We will obtain three variables B,C and D at selection lines and also A as i
Q. Illustrate TCP - IP Networking Model? TCP/IP is an acronym for Transmission Control Protocol / Internet Protocol. It is a collection of applications, protocols and services.
State and prove Demorgan's second theorem Proof: Demorgan's second theorem = A‾ + B‾ The two sides of the equation here = A‾ + B‾ is represented through the logic d
Contraposition : The contraposition equivalence is as follows: So it may seem a small strange at first, this means that it appears which we have said nothing in the f
Connectives in first-order logic sentences - Artificial intelligence We may string predicates together into a sentence in the same way by utilising connectives that we did for
What is the use of boot block? For a computer to start running when powered up or rebooted it needs to have an initial program to run. This bootstrap program tends to be simple
Learning Weights in Perceptrons In detail we will look at the learning method for weights in multi-layer networks next chapter. The following description of learning in percept
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