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N OT E The problem with SP2 in which the entire Internet was defined as your Local Zone was reported in September 2004, according to Microsoft, and fixed in December. Because it was a configuration issue the software was doing precisely what it had been told to do it wasn t considered a bug. (See Microsoft Knowledge Base Article 886185.)

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If the curvatures cx and cy, are equal to c, this expression becomes identical to Eq. (18.1). This expression is symmetrical with respect to x and also with respect to y. As a result, if x and y as well as cx and cy are interchanged, the form of this expression is preserved. Another interesting property of this surface is that the cross section in a plane containing the optical axis is always a circle, with a curvature cy given by the Euler formula. The sphero-cylindrical and the toroidal surfaces have in common that their cross sections in the x-z and y-z planes are circles. An important difference between the sphero-cylindrical and the toroidal surface is that the rst has only two possible solutions for z since there is only one square root. For the toroidal surface we have two square roots, one inside the other. For a spindle toroid two of the four solutions may be imaginary.

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values; for example, a real variable can take any value in the range [l, u]; an integer variable can take any integer value in the range [l, u], and a logical variable can take the value 0 or 1. Domain reduction systematically removes values that are no longer valid from each variable domain. If there is a suf cient number of constraints, the domains may be dramatically reduced. If a variable has an empty domain, the problem becomes infeasible, meaning that there is no possible value for that variable, so the problem has no solution. Constraint propagation works by systematically reducing all variable domains. Each constraint is linked to an associated set of variables that are affected by that constraint. Each variable belongs to the associated set of at least one constraint; if not, it is an unconstrained variable. If the domain of that variable is altered, the associated set of variables of each of these constraints will also be affected. This change to their domains will, in turn, affect other variables via other constraints. The effect of a change in one variable is propagated via constraints throughout all the decision variables. The effectiveness of this approach increases as the network of constraints expands. Example. Consider three variables X, Y, Z with: domain X {1 . . . 5} domain Y {1 5} domain Z {1 5} constraint C1: X . Y constraint C2: X Z 4 Apply domain reduction: domain ) domain C2 domain ) domain C1 C2 domain ) domain domain C1 X Y X Z X Y Z {2 5} {1 4} {1 3} {1 3} {2 3} {1 2} {1 2}

An example is shown for k = 8, n = 10, and N = 25 in Figure 6.25(b). The central moments may be obtained from the characteristic function or directly. The mean and variance are

The item numbered <5> in Figure 36-1 is what you entered in the Console. The item labeled [2] (+ 1 a 3) is where the error occurred, while <1> :ERROR-BREAK signaled the function s termination because of the error. Visual LISP enables you to find the source position (the line of code that produced the error) and the call source point (the position in your code where the function was called) for the error. To find them, right-click the third item in the Error Trace window. From the shortcut menu, you can choose either Source Position or Call Source Point. Jumping to the position in your code where the function was called is extremely handy when debugging a large application.

If the Hessian matrix d2f/dtdtT in this expression is positive definite, the point AtNE is a minimum of f ( t c At). If it is negative definite, it is a maximum. If it is indefinite, AtNE is a saddle point. If f ( t ) is quadratic, f(t, At) and f ( t c At) coincide and the Newton method converges in one step to this minimum, maximum, or saddle point. Generally, the direction of the Newton step is a descent direction if

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