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Figure 34-1: Hierarchy of HTML Server controls HTML Server controls map directly to their corresponding HTML elements. When converting ASP 3.0 pages to ASP.NET pages, using HTML Server controls is a lesspainful solution than using ASP.NET's Web controls (discussed in the next chapter). Table 34-1 describes these controls in more detail.
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Visitors. You can view the number of visitors by day as well as the number of page views, time onsite, bounce rate (percentage of visitors who leave after looking at one page), and more. You can drill-down into the numbers here to discover the operating systems, browsers, screen resolutions, and languages used while visiting. Traffic sources. You can see where the traffic to your site is coming from. Some of your traffic will come from direct sources people typing the name of your site into the location bar. Other sources include referring sites: other sites that link to yours as well as search engines, such as Google. This section of the system shows specific sources, ranked by the number of links that are sent your way. You can also view the search keywords that are used to find your site. Content. You can see the most popular pages on your site. The pages that receive the most traffic are listed here, and you can also see the most popular entrance pages the pages most often landed on by new visitors as well as the exit pages where they leave. You can also view a site overlay, showing the number of clicks on every hyperlink throughout the site. Goals. You can set up goals to determine whether visitors are reaching certain parts of your site. For example, you may have a registration form. If a completed form is worth something to you say, having a registered user on your site has a dollar value you can establish that form s thank-you page as the goal. When that page is visited, you have met a goal, and with a dollar value attached, you can readily determine how much money your site is generating. Take some time to explore the functionality that Google Analytics makes available. As a web developer with clients, I often use this tool to determine how their sites are faring. My clients also appreciate receiving the reports that Google Analytics generates; every report includes an Export function that generates a PDF or spreadsheet document, ready to send to anyone who wants it.
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that has a capacity of 800 area codes and 800 exchange codes. To support competition by new long-distance carriers after the 1984 divestiture, a four-digit carrier identi cation code CIC(4) may be inserted before the called party number to route the call through the long-distance carrier identi ed by the CIC(4) instead of going through the presubscribed IXC. Pre xes. In order to expedite the setup of a connection, there are situations in which a subscriber has to dial one or more pre x digits ahead of the called party address. For example, since AC(3) and EC(3) codes use the same format, an exchange would have to perform a time-out after receiving the seventh digit to distinguish a subscriber number from a national number. Therefore, subscribers must dial the pre x 1 to indicate that the called address is a NN, while pre x 011 indicates that the address is an international number. Similarly, the pre x 101 must he dialed when a carrier identi cation code is inserted before the called party number. More details on pre xes are found in Section 3.7.1. 1.2.2 Other National Numbering Plans
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The estimates t and V are consistent and asymptotically normal under relatively mild assumptions, and proofs can be found along the lines of Sections 6.2 and 6.3. While the consistency proof is complicated [the main problem being caused by the fact that we have a simultaneous location-scale problem, where assumptions (A-5) or (B-4) fail], asymptotic normality can be proved straightforwardly by verifying assumptions (N-1) - (N-4). course, this imposes some regularity conditions on w, u, 2 and Of and on the underlying distribution. Note in particular that there will be trouble if U(T)/T is unbounded and there is a pointmass at the origin. For details, see Maronna (1976) and Schonholzer (1979). The asymptotic variances and covariances of the estimates coincide with those of their influence functions, and thus can easily be derived from (8.69) and (8.75). For symmetry reasons, location and covariance estimates are asymptotically uncorrelated, and hence asymptotically independent. The location components ij are asymptotically independent, with asymptotic variance (8.77) The asymptotic variances and covariances of the components of V can be described as follows (we assume that V is lower triangular):
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SELECT CONVERT(NVARCHAR(15),Person.DateofBirth,1) AS Date, Person.FirstName AS Name, Person.Gender AS G, ISNULL(F.FirstName + + F.LastName, * unknown * ) as Father, M.FirstName + + M.LastName as Mother FROM dbo.Person Left Outer JOIN dbo.Person F ON Person.FatherID = F.PersonID INNER JOIN dbo.Person M ON Person.MotherID = M.PersonID ORDER BY Person.DateOfBirth
Introduction to Web Development
Automatic coincident relation
As we have seen, one of the three modules currently implemented in Sesame is an RQL query engine. In Sesame, a version of RQL was implemented that is slightly different from the language proposed by Karvounarakis et al. (2000). The Sesame version of RQL features better compliance to W3C speci cations, including support for optional domain and range restrictions as well as multiple domain and range restrictions. It does not, however, feature support for data typing as proposed in the original language proposal. See Broekstra and Kampman (2001b) for details. The Query Module follows the path depicted in Figure 5.4 when handling a query. After parsing the query and building a query tree model for it, this model is fed to the query optimizer, which transforms the query model into an equivalent model that will evaluate more ef ciently. These optimizations mainly consist of a set of heuristics for query sub-clause move-around. Notice that these pre-evaluation optimizations are not dependent on either the domain or storage method. The optimized model of the query is subsequently evaluated in a streaming fashion, following the tree structure into which the query has been broken down. Each object represents a basic unit in the original query and evaluates
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