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)
One, right? Because there's just the blank title slide that automatically pops up.
Answer: In external hashing the hash table is in disk where each slot of the page table holds multiple entries which refers to pages on the disk organised in the form of buckets.
B-trees are self balancing trees which contains sorted data and allows insertion, deletion, traversals
Traversal is the process of visiting the nodes of the tree data structure.
Explanation:
External hashing is different from internal hashing and it refers to concepts in database management systems. Internal hashing stores only single record maintained in page table format, whereas external hashing holds multiple entries.
B-trees are generalisation of binary trees where it can have more than 2 children.
Traversal of trees helps in insertion, deletion, modification of nodes in tree data structure
The combination of a transmitter and a receiver in a single cell package is a transceiver
All of the above is the answer
