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trend, important features of interest (eg, stationarity of the increments) are likely to be lost, thus impairing the estimation of the relevant scaling parameters Power-law trends can even mimic LRD correlations when added to a stationary short-range process, leading to entirely erroneous conclusions [5, 17, 65] It is therefore desirable, prior to any analysis, to eliminate possible trends or, at least, to be able to evaluate and control their effects on the nal estimates: wavelets offer a versatile and easy way of doing so In order to understand where the effectiveness of wavelets comes from in the context of trend removal, it is worthwhile to start from the admissibility condition, Eq (21), satis ed by any wavelet c0 : saying that a wavelet is zero-mean is in fact equivalent to saying that it is orthogonal, and therefore ``blind,'' to nonzero mean values.

All of the documentation to this point is instructive in nature. Each one should leave little doubt as to what the architecture team has in mind. Each level further narrows the scope of the design and operation of the information technology systems. As you move down the group of documents, you see that they leave less room for discretion in how the systems should look, function, and work together. Guidelines are the tools that allow room for the creative art needed within systems and provide space for discretion both in implementation and in operations. They permit some originality and judgment within limits that are not in conflict with the policies or standards that preceded them. The limits are contained in the guidelines. A good example of the nature of guidelines is troubleshooting lists or charts. Guidelines are general and suggestive in nature; they aren t precisely stated requirements in the way standards are. Guidelines are best used where there may be more than one good or acceptable way to do something. In a practical sense, they become optional paths to a desired outcome. (Please refer to Appendices for examples.)

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Many Net-savvy people are aware of a simple trick that allows users to forge electronic mail. This is accomplished by talking directly to the SMTP daemon on port 25 of a server machine. The mail-forging attack takes advantage of the fact that mail-serving hosts monitor port 25 for incoming Simple Mail Transfer Protocol (SMTP) messages. One of the Internet rites of passage is to telnet to port 25 and send fake mail to a friend. This game is very well known; however, the scheme is easily debunked. The SMTP daemon actually marks the forged mail with the IP number of the machine that connected to port 25, which makes it very easy to discern which machine sent the mail.3 Spammers often forge mail headers so that the true source of a spam message is hard to discern. It is usually easy to detect forged mail by looking carefully at the header. The machine listed in the From line should be the same as the Received: line. Most users and mail readers look only at the From line; systems people know to look at both. Note that some legitimate mail may have differing From and Received: lines, depending on how people send their mail. Here is an example of mail forged by an author on his home machine (tigger.mediasoft.net) to his own work account. Note how the From and Received: lines differ.

A natural generalization consists of considering wavelets with more than one vanishing moment, in the sense of Eq (25), since assuming that the number of vanishing moments is N allows the analysis to be blind to polynomials of order up to N 1 In other words, the removal of a polynomial trend of order p is guaranteed by a wavelet with N ! p 1 From a practical point of view, when p is the unknown order of a polynomial approximation of a trend, trend removal amounts to analyzing the data with different wavelets such that N 1; 2; Until the effective value N p 1 is reached, the analysis is governed by the trend and gives N-dependent results, whereas, as soon as N ! p 1, stabilized results are obtained and reveal relevant features of the detrended data.

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