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Gierk et al. (2015) [9] compared the psychometric properties of the SSS-8 and the PHQ-15 in a sample of 131 psychosomatic patients. The sum scores of both questionnaires showed a very high correlation (r = 0.83). The internal consistency was comparable (SSS-8 Cronbach's α = 0.76 vs. PHQ-15 Cronbach's α = 0.80).
The form is YYXXDD/SSSC, where XX=MM (month of birth) for male (numbers 01–12) and XX=MM+50 for female (numbers 51–62), SSS is a serial number separating persons born on the same date and C is a check digit, but for people born before 1 January 1954 the form is without the check digit - YYXXDD/SSS.
In cryptography, pseudorandom noise (PRN [1]) is a signal similar to noise which satisfies one or more of the standard tests for statistical randomness. Although it seems to lack any definite pattern , pseudorandom noise consists of a deterministic sequence of pulses that will repeat itself after its period.
In the United States, a Social Security number (SSN) is a nine-digit number issued to U.S. citizens, permanent residents, and temporary (working) residents under section 205(c)(2) of the Social Security Act, codified as .
Generally abbreviated to "P.R.N." or "PRN", pro re nata refers to the administration of prescribed medication whose timing is left to the patient (in the case of patient-controlled analgesia), nurse, or caregiver, as opposed to medication that is taken according to a fixed (primarily daily) schedule (a.k.a. "scheduled dosage").
A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG), [1] is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers.
A UCC-1 financing statement (an abbreviation for Uniform Commercial Code-1) is a United States legal form that a creditor files to give notice that it has or may have an interest in the personal property of a debtor (a person who owes a debt to the creditor as typically specified in the agreement creating the debt).
A probabilistic neural network (PNN) [1] is a feedforward neural network, which is widely used in classification and pattern recognition problems.In the PNN algorithm, the parent probability distribution function (PDF) of each class is approximated by a Parzen window and a non-parametric function.