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NP can be defined similarly using nondeterministic Turing machines (the traditional way). However, a modern approach uses the concept of certificate and verifier. Formally, NP is the set of languages with a finite alphabet and verifier that runs in polynomial time. The following defines a "verifier": Let L be a language over a finite alphabet, Σ.
Acoustic impedance, denoted Z and measured in Pa·m −3 ·s in SI units, is defined by [2] = ^ ^ (), where ^ is the Laplace transform of sound pressure, [citation needed] ^ is the Laplace transform of sound volume flow rate.
133 Pa 1 torr ≈ 1 mmHg [34] ±200 Pa ~140 dB: Threshold of pain pressure level for sound where prolonged exposure may lead to hearing loss [citation needed] ±300 Pa ±0.043 psi Lung air pressure difference moving the normal breaths of a person (only 0.3% of standard atmospheric pressure) [35] [36] 400–900 Pa 0.06–0.13 psi
co-NP contains those problems that have a simple proof for no instances, sometimes called counterexamples. For example, primality testing trivially lies in co-NP, since one can refute the primality of an integer by merely supplying a nontrivial factor. NP and co-NP together form the first level in the polynomial hierarchy, higher only than P.
If P and NP are different, then there exist decision problems in the region of NP that fall between P and the NP-complete problems. (If P and NP are the same class, then NP-intermediate problems do not exist because in this case every NP-complete problem would fall in P, and by definition, every problem in NP can be reduced to an NP-complete ...
A problem is NP-complete if it is both in NP and NP-hard. The NP-complete problems represent the hardest problems in NP. If some NP-complete problem has a polynomial time algorithm, all problems in NP do. The set of NP-complete problems is often denoted by NP-C or NPC.
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In statistical quality control, the np-chart is a type of control chart used to monitor the number of nonconforming units in a sample.It is an adaptation of the p-chart and used in situations where personnel find it easier to interpret process performance in terms of concrete numbers of units rather than the somewhat more abstract proportion.