Answer:
the galactic network.
have a nice day <3
Explanation:
increase power in the telephone industry. investigate technologies for the military in the US. he first idea for a communications network was called: the galactic network.
Answer:
A register
Explanation:
Registers are small memory used to store data or values and supply them to the processor as and when needed. These register hold the data temporarily and hold small units of program instructions. So whenever the CPU wants to work on data they have to be made available through the registers. Even after a arithmetic operation the registers serve as buckets for holding the value.
There are different types of registers such as register A, B, C etc and these registers lie in close proximity to the CPU so that we could provide the data immediately and much faster when asked by the CPU.
Therefore we can say that registers are used to temporarily hold small units of program instructions and data immediately before, during, and after execution by the central processing unit (CPU).
To complete the sentence - Methods can be overload methods correctly by providing different parameter lists for methods with the same name.
Thank you for posting your question here at brainly. I hope the answer will help you. Feel free to ask more questions.
Answer:
Nonexclusive forwarding
Explanation:
In Nonexclusive forwarding, DNS forwarding is setup so that if the DNS server receiving the forwarded request cannot resolve the name, then the server that originally forwarded the request makes an attempt to resolves it. If that fails, the server sends a request to its designated forwarder.
Answer:
Explanation:
A general idea is that you should repeat the simulation until the results converge. An easy but illustrative example of this is that we want to see if the R function rbinom is accurate in simulating a coin toss with a given probability. We will simulate one coin toss 10000 times, and plot the percentage of heads against the number of coin tosses:
set.seed(1)
n <- 10000
result <- NULL
percent <- NULL
for (i in 1:n) {
result[i] <- rbinom(1,1,0.5)
percent[i] <- sum(result)/i
}
plot(seq(1:10000),percent, type="l")
abline(0.5, 0, lty=2)
