Following are the various algorithms time complexities expressions. Find the dominant terms and specify the Big-Oh complexity of each algorithm.S. No.ExpressionDominant term(s)O (. . .)1.75 + 0.001n1.3 + 0.025n + (1000)4 2.500n + 100n + 50n log10 n 3.(10n1.5)4 + 0.3n + 5n6.5 + 2.5 · n2.75 4.150n3 + n2 log2 n + n(log2 n)4 5.3 log10 n + log2 log2 n 6.100n4 + 0.01n2 + 200(log2 n)4 7.n3 + 0.01n + 100n2 + 5n3 8.2n0.5 + n0.35 + 0.5n0.25 9.0.01n2 log2 n + n(log2 n) 10.50n3 log3 n + n5 log3 n + 100n4 Following are the various algorithms time complexities expressions. Find the dominant terms andspecify the Big-Oh complexity of each algorithm.Expression75 + 0.001n.3 +0.025n + (1000)500n + 100n + 50n log1o n(10n1.5)4 +0.3n + 5nº.5 + 2.5 · n².75150n3 + n² log2 n+n(log2 n)*3 log10 n + log2 log, n100n4 + 0.01n² + 200(log2 n)n3 + 0.01n + 100n? + 5n32n0.3 +n0.35 +0.5n0.250.01n² log2 n + n(log2 n)50n3 log3 n + n log3 n + 100ntS. No.Dominant term(s)O(.)1.2.3.4.5.6.7.8.9.10.

Answer: 1. Dominant Term: n1.3 O(..)=O(n) 2. Dominant Term:50n log10 n O(..)=O(nlog(n)) 3. Dominant…

Answered: Following are the various algorithms…

Following are the various algorithms time complexities expressions. Find the dominant terms and specify the Big-Oh complexity of each algorithm.

C++ Programming: From Problem Analysis to Program Design

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Computational Systems

The computation systems can be defined as the systems that are capable of solving a problem that includes calculations either mathematical or logical, and are able to produce the result as an output. For example, a simple calculator that is given a set of numbers and operators as input and produces the result as an output can be defined as a computational system. The above example is a simple illustration only, the computational systems range from simple devices to complex devices such as the systems that control the SpaceX companies, Starlink satellites which are being quite recently seen in the skies at many places globally.

Question

Following are the various algorithms time complexities expressions. Find the dominant terms and specify the Big-Oh complexity of each algorithm.

S. No.	Expression	Dominant term(s)	O (. . .)
1.	75 + 0.001n^1.3 + 0.025n + (1000)⁴
2.	500n + 100n + 50n log₁₀ n
3.	(10n^1.5)⁴ + 0.3n + 5n^6.5 + 2.5 · n^2.75
4.	150n³ + n² log₂ n + n(log₂ n)⁴
5.	3 log₁₀ n + log₂ log₂ n
6.	100n⁴ + 0.01n² + 200(log₂ n)⁴
7.	n³ + 0.01n + 100n² + 5n³
8.	2n^0.5 + n^0.35 + 0.5n^0.25
9.	0.01n² log₂ n + n(log₂ n)
10.	50n³ log₃ n + n⁵ log₃ n + 100n⁴

Following are the various algorithms time complexities expressions. Find the dominant terms and
specify the Big-Oh complexity of each algorithm.
Expression
75 + 0.001n.3 +0.025n + (1000)
500n + 100n + 50n log1o n
(10n1.5)4 +0.3n + 5nº.5 + 2.5 · n².75
150n3 + n² log2 n+n(log2 n)*
3 log10 n + log2 log, n
100n4 + 0.01n² + 200(log2 n)
n3 + 0.01n + 100n? + 5n3
2n0.3 +n0.35 +0.5n0.25
0.01n² log2 n + n(log2 n)
50n3 log3 n + n log3 n + 100nt
S. No.
Dominant term(s)
O(.)
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.

Process or set of rules that allow for the solving of specific, well-defined computational problems through a specific series of commands. This topic is fundamental in computer science, especially with regard to artificial intelligence, databases, graphics, networking, operating systems, and security.

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