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Several new features are added to the document. The rst immediate change is the addition of the XML declaration at the top of the document. The insertion < xml version= 1.0 > declares that the following document is an XML document and should be treated with the rules used with any XML document. Following the XML declaration is a DOCTYPE that declares what DTD is being used. Following the strict translation of XHTML, the DOCTYPE is html PUBLIC -// W3C//DTD XHTML 1.0 Strict//EN . There are three types of XHTML: Strict, Transitional, and Frames. XHTML-Strict is the implementation of XHTML as de ned in the complete XHTML 1.0 standard. XHTML-Transitional is a de nition of XHTML that enables HTML 4.0 tags to be used within the syntax, enabling a transition from one language to the next. XHTML-Frames is a version of the language that enables Netscape Frames to be used within XHTML-formatted Web pages. The line http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd directs the browser to download the appropriate DTD le to translate the document. The XHMTL name space is de ned within the <HTML> tag, identifying where the name space is located on the Internet. Formatting can t be done with the <font> and <body> tags in XHTML. A cascading style sheet replaces the tags in the rst version of the document. The <body> background color and default text color are identi ed as white (#FFFFFF) and black (#000000), respectively. The presentation style for the <P> tag is de ned as font Arial and size 14 point.

Purpose: Returns the binary (base 2) logarithm of the expression. Syntax: Lg (expression) where expression is a positive numeric expression or the name of a field containing a positive numeric value. Example: The following expression returns 6:

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, x(k k0 ) x(k k0 ) , k k0 : T(k) 1 because this requires x 2x p 2 x, implying p 2x. Thus, T maps the integers =x into all of Zp except for the single value 1 so that & ' K x 1 [ QUAD p % , Pr K x 2 where K denotes the random choice in Step 13.4a. k x Finally, k x is a quadratic residue modulo p if and only if both or neither k x and k 2 x are quadratic residues modulo p, which completes the proof of Proposition 13.4. Berlekamp s Algorithm can be applied to compute quadratic residues modulo N pq, where p and q are odd primes. If N is the product of two primes, there are four solutions. Why four Proposition 13.6 (The Chinese Remainder Theorem)2: i k.

And, of course, the central computer must be able to be configured with the total amount of ports needed for remote site connectivity This last requirement was not usually a problem, especially in the IBM mainframe environment But what if the number of remote sites grew to 10 20 100 How many links and ports would be needed to deploy such a hierarchical network then As corporations and the corporate networks merged, expanded, and otherwise grew throughout the 1970s and into the 1980s, this became a real issue for corporate data network designers Fortunately, it is not necessary to draw detailed pictures of these larger networks to figure out exactly how many links and ports are needed There is a simple mathematical relationship that can be used to figure out how many links and ports would be needed to link any number of sites into a hierarchical, star-shaped network.

SELECT AVG(pen) as estpenetration FROM (SELECT TOP 5 SQRT(SQUARE((collegep - collegep10007)/stdcollp) + SQUARE((hhmi - hhmi10007)/stdhhmi)) as dist, oz.* FROM (SELECT oz.*, AVG(hhmi) OVER () as avghhmi, STDEV(hhmi) OVER () as stdhhmi, AVG(collegep) OVER () as avgcollegep, STDEV(collegep) OVER () as stdcollp, MAX(CASE WHEN zipcode = 10007 THEN hhmi END ) OVER () as hhmi10007, MAX(CASE WHEN zipcode = 10007 THEN collegep END ) OVER () as collegep10007 FROM (SELECT o.zipcode, MAX(hhmedincome) as hhmi, MAX(popedubach + popedumast + popeduprofdoct ) as collegep, COUNT(DISTINCT householdid)/MAX(hh*1.0) as pen FROM orders o JOIN customer c ON o.customerid = c.customerid JOIN zipcensus zc ON o.zipcode = zc.zipcode WHERE zc.hh >= 1000 GROUP BY o.zipcode) oz ) oz WHERE zipcode <> 10007 ORDER BY 1) score

Existing customers pose a different challenge from new starts. Obtaining historical revenue is simply a matter of adding up the revenue that existing customers have paid. For future revenue, there is a hitch. Existing customers are not starting at tenure zero, because these customers are active now and have a particular tenure. So, direct application of survival values is not the right approach. The solution is to use conditional survival, that is, survival conditioned on the fact that customers have already survived up to their current tenure.

At this point the relational Sales database is complete and ready to use You will find many databases essentially just like this one in use in the real world, and for many purposes they are just fine However, for certain types of analysis with a really large database, this sort of structure is not ideal Here s where the idea of multidimensional data comes into play Let s take a look as this relates to the sample data As designed, the database includes a table for salesmen and another for customers But perhaps you want to analyze the relationship between salesmen and customers You may think that certain salespeople do better with certain customers Perhaps Gomez does really well selling to Acme Metal Works but not so well with East End Inc.

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