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A font refers to the style and appearance of the words you type in a wordprocessor or similar program. A little-known fact about fonts is that having too many of them increases the time it takes for Windows to start. If you have a large collection of fonts but don t want to delete any, then do the following:

Thus, we need a way of estimating the thickness Fortunately, a natural approach is suggested by Lemma 5 Namely, given an estimate for the thickness, say e, construct a class consisting of all of the nodes of degree not exceeding e If the number of nodes in the class is at least ( 6)n/ , then all is well If, on the other hand, the number of nodes is less than ( 6)n/ , then the current value of e is less than the actual thickness, and the value of e is increased before forming the next class The process continues in this fashion with: classes being formed; the size of the class compared to the known bound; and, if the class is too small, then the estimate of the thickness increased.

Next, the following define the outlets for the CommandWindowController class that will be hooked up with other objects.

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e 0.54778 e g(x) = = 0.3664 g(x) 1+e 1 + e 0.54778 The estimated probability that a customer with 300 day minutes will churn is over 36%, which is more than twice the overall proportion of churners in the data set, indicating that heavy-use customers have a higher propensity to churn. The deviance difference G for this example is given by

The only care that needs to be taken is to not increase the estimate too quickly (it would make classes very large and not spread nodes among classes) or too slowly (there will be too many classes, hence too many passes over the network will have been made) Fortunately, it is possible to increase the estimate of at an intermediate pace that is satisfactory from both points of view These ideas form the basis of the proof given in [17] that establishes: Lemma 6 DBS makes O(log n) passes over the graph This lemma and a careful examination of DBS provides: Lemma 7 For arbitrary graphs, the running time of DBS is O(n log n + n 2) 16513 An Approximation Ratio for DBS Theorem 10 For a graph of thickness , DBS has an approximation ratio of O( ).

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Automation . . . . . . . . . . . . . . . . . . . . . Working with foreign objects . . . . . . . . Early versus late binding . . . . . . . . . . A simple example . . . . . . . . . . . . . . . Controlling Word from Excel . . . . . . . . Controlling Excel from another application Working with ADO . . . . . . . . . . . . . . . . . Using SendKeys . . . . . . . . . . . . . . . . . . .

Equality of matrices: Two (m x n) matrices A = [aij] and B = [bill are equalifaij=bijfori=l, ... ,TTl,j 1, .. ,no Equivalent matrices: The (m x n) matrices A and B are equivalent if nonsingular matrices C (m x TTl) and D (n x n) exist such that B = CAD. (For examples see 6.) Equivalent polynomial matrices: Two polynomial matrices P(x) and Q(x) are said to be equivalent if unimodular polynomial matrices U (x) and V(x) exist such that P(x) U(x)Q(x)V(x). (See Section 11.3.)

The difference g(p, q) between the two sides is g(p, q) = p log Then dg(p, q) p 1 p 4 = + 2(q p) (11.141) dq q ln 2 (1 q) ln 2 2 ln 2 = 4 q p (q p) q(1 q) ln 2 ln 2 (11.142) (11.143) p 1 p 4 + (1 p) log (p q)2 . q 1 q 2 ln 2 (11.140)

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