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For instance, the UPC-A barcode for a box of tissues is "036000241457". The last digit is the check digit "7", and if the other numbers are correct then the check digit calculation must produce 7. Add the odd number digits: 0+6+0+2+1+5 = 14. Multiply the result by 3: 14 × 3 = 42. Add the even number digits: 3+0+0+4+4 = 11.
A standard example of mutual recursion, which is admittedly artificial, determines whether a non-negative number is even or odd by defining two separate functions that call each other, decrementing by 1 each time. [3] In C:
the use of 2 to check whether a number is even or odd, as in isEven = (x % 2 == 0), where % is the modulo operator; the use of simple arithmetic constants, e.g., in expressions such as circumference = 2 * Math.PI * radius, [1] or for calculating the discriminant of a quadratic equation as d = b^2 − 4*a*c
The odd–even sort algorithm correctly sorts this data in passes. (A pass here is defined to be a full sequence of odd–even, or even–odd comparisons. The passes occur in order pass 1: odd–even, pass 2: even–odd, etc.) Proof: This proof is based loosely on one by Thomas Worsch. [6]
This algorithm is sometimes also known as the crossing number algorithm or the even–odd rule algorithm, and was known as early as 1962. [3] The algorithm is based on a simple observation that if a point moves along a ray from infinity to the probe point and if it crosses the boundary of a polygon, possibly several times, then it alternately ...
In the even–odd case, the ray is intersected by two lines, an even number; therefore P is concluded to be 'outside' the curve. By the non-zero winding rule, the ray is intersected in a clockwise direction twice, each contributing −1 to the winding score: because the total, −2, is not zero, P is concluded to be 'inside' the curve.
In decision theory, the odds algorithm (or Bruss algorithm) is a mathematical method for computing optimal strategies for a class of problems that belong to the domain of optimal stopping problems. Their solution follows from the odds strategy , and the importance of the odds strategy lies in its optimality, as explained below.
As a running example, we consider a 10×10 magic square, where we have divided the square into four quarters. The quarter A contains a magic square of numbers from 1 to 25, B a magic square of numbers from 26 to 50, C a magic square of numbers from 51 to 75, and D a magic square of numbers from 76 to 100.