Two or more computers connected together is referred to as a network.
So the answer is <span>B. network.</span>
Answer and Explanation:
The compression rate says by how much the text was compressed from the original as a percentage. Don't forget that the compressed version of the text is the compressed text size + dictionary size.
From the given picture:
compressed text size = 17 bytes
dictionary size = 26 bytes
compressed text size + dictionary size = 17 + 26 = 43 bytes
original test size = 58 bytes
compression rate as percentage = (43 / 58) * 100 = 74.14% ( rounded to two decimal )
Space savings = 100 - compression rate
= 100 - 74.14 = 25.86%
Is this a "good" compression rate? Why or why not?
Compression data is a heuristic problem. It’s hard to say the exact compression rate that is good or bad. If you feel satisfied by ~ 26% of compression, then it is a good compression rate.
The compression rate above frees up 26% space for you, so that you can put additional information
without losing information. In that way it is a good compression rate.
A belief is an attitude that something is the case, or that some proposition about the world is true.[1] In epistemology, philosophers use the term "belief" to refer to attitudes about the world which can be either true or false.[2] To believe something is to take it to be true; for instance, to believe that snow is white is comparable to accepting the truth of the proposition "snow is white". However, holding a belief does not require active introspection. For example, few carefully consider whether or not the sun will rise tomorrow, simply assuming that it will. Moreover, beliefs need not be occurrent (e.g. a person actively thinking "snow is white"), but can instead be dispositional (e.g. a person who if asked about the color of snow would assert "snow is white").[2]
There are various different ways that contemporary philosophers have tried to describe beliefs, including as representations of ways that the world could be (Jerry Fodor), as dispositions to act as if certain things are true (Roderick Chisholm), as interpretive schemes for making sense of someone's actions (Daniel Dennett and Donald Davidson), or as mental states that fill a particular function (Hilary Putnam).[2] Some have also attempted to offer significant revisions to our notion of belief, including eliminativists about belief who argue that there is no phenomenon in the natural world which corresponds to our folk psychological concept of belief (Paul Churchland) and formal epistemologists who aim to replace our bivalent notion of belief ("either we have a belief or we don't have a belief") with the more permissive, probabilistic notion of credence ("there is an entire spectrum of degrees of belief, not a simple dichotomy between belief and non-belief").[2][3]
Beliefs are the subject of various important philosophical debates. Notable examples include: "What is the rational way to revise one's beliefs when presented with various sorts of evidence?"; "Is the content of our beliefs entirely determined by our mental states, or do the relevant facts have any bearing on our beliefs (e.g. if I believe that I'm holding a glass of water, is the non-mental fact that water is H2O part of the content of that belief)?"; "How fine-grained or coarse-grained are our beliefs?"; and "Must it be possible for a belief to be expressible in language, or are there non-linguistic beliefs?".[2]
Answer:
I would select Straight 2-way Merge sort over Quicksort when:
C. If space were not an issue If I knew the size of the data set was very large.
Explanation:
For large datasets, the Straight 2-way Merge sort has been found to be more efficient than the Quicksort. It also works faster than Quicksort. However, Quicksort has been found to be more efficient, working faster than the Straight 2-way Merge sort with small datasets. The two are algorithms for sorting. While Straight 2-way Merge Sort uses two streams with repetitions, the Quicksort uses just one stream without repetitions and additional storage space.
