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1: Defining the Enterprise The XML project For XML projects, it is best to start with an already known XML DTD, particularly if you are not familiar with XML itself. This will eliminate one point where you might get something wrong. A good place to look for sample DTDs is at the W3C site (http://www.w3c.org/) and the XML sites (http://www.xml.org/ and http://www.xmlhack.com/). Cross Reference A whole part of this book is devoted to understanding XML as a document as well as the APIs used to read and write it. Check out Part IV, "Communicating Between Systems with XML," for all the XML information.

The main result in this chapter is to prove the convergence of the Rice series in a general framework instead of considering only some particular processes This provides a method that can be applied to a large class of stochastic processes A typical situation given by Theorem 56 states that if a stationary Gaussian process has a covariance with a Taylor expansion at zero that is absolutely convergent at t = 2T , then FMT (u) can be computed by means of the Rice series On the other hand, even though Theorems 51 and 57 do not refer speci cally to Gaussian processes, for the time being we are able in practice to apply them to the numerical computation of FMT (u) only in Gaussian cases Section 5.

In general therefore option (3) seems to be the design most likely to fulfil general requirements for longitudinal information, but has difficulties of both methodology and interpretation. In using option (1) or (2) in its place, there is a clear need to explain the limitations of what can be inferred to users of the information noting however that there is a risk that such limitations may be ignored by users, particularly if no other information is available. 2.3.2 Target Variables

3 includes a comparison of the complexities of the computation of FMT (u) using the Rice series versus the Monte Carlo method, in the case of a general class of stationary Gaussian processes It shows that use of the Rice series is a priori better More important is the fact that the Rice series is self-controlling for numerical errors This implies that the a posteriori number of computations.

A tree is made up of a series of decision points, where the entire set of observations or a subset of the observations is split based on some criteria. Each point in the tree represents a set of observations and is called a node. The relationship between two nodes that are joined is de ned as a parent-child relationship. The larger set which will be divided into two or more smaller sets is called the parent node. The nodes resulting from the division of the parent are called child nodes as shown in Figure 6.34. A child node with no more children (no further division) is called a leaf node and shown in Figure 6.35.

Calling the create() method on the home interface establishes a session to be used: From now on, you call methods on the session. These method calls now become a listing of the tasks we mentioned a short time ago:

It is interesting to compare different approaches in terms of implementational issues. For example, in PHASAR type of devices with waveguides on a plane, the lengths of the waveguides should be chosen according to the following equations: (a) Plane reference wave only, automatic zero-crossings: Li axi (b) Plane reference wave only, negative phase implementation Li axi yi =k where yi is the desired phase, and k is the wave number. (c) Plane and spherical reference waves, automatic zero-crossings Li a xi rci 19:6-3 19:6-2 19:6-1

We restrict this section to the KSS model. In this case, a few asymptotic results have been proved on variances, when the number m of unknowns tends to . More precisely, consider the normalized random variable NX nX = . D It is an obvious consequence of Theorem 12.1 that E(nX ) = 1. Let us denote 2 m,d = Var(nX ). We have: Theorem 12.2. Assume that the random polynomial system (12.1) is a KSS system with common degree equal to d, d 2, and assume that d d0 < , where d0 is some constant independent of m. Then, as m + :