barcode vb net Towards the Semantic Web in .NET

Integrating qr barcode in .NET Towards the Semantic Web

where n is the number of nodes to be interconnected. If there are eight nodes, as illustrated in Figure 5.1, the number of trunks required is calculated as 28 = 8(8 1) 2

Although guide curves can be longer than the loft, they can not be shorter. The guide curve applies to the entire loft. If you need to apply the guide curve only to a portion of the loft, then split the loft into two lofts: one that uses the guide curve and one that does not. The guide curve must intersect all profiles in a loft. If you have more than one guide curve, the order in which they are listed in the box is important. The first guide curve helps to position the intermediate profiles of the loft. It may be difficult to visualize the effects of guide-curve order before it happens, but remember that it does make a difference, and depending on the difference between the curves, the difference may or may not be subtle. Guide curves are also used in sweeps, which I address later in this chapter. Figure 7.12 shows a model that is lofted using guide curves. The image to the left shows the sketches that are used to make the part. There are two sketches with points; you can use points as loft profiles. The image in the middle shows the Loft feature without guide curves, and the one to the right is the part with guide curves. If you would like to examine how this part is built, you can find it on the CD-ROM with the filename 7 Guide Curves.sldprt.

SELECT Fable.Title, FTS.Rank FROM Fable JOIN CONTAINSTABLE (Fable, *, Lion ) FTS ON Fable.FableID = FTS.[KEY] ORDER BY FTS.Rank DESC

The book example uses a dark gray, which has a hex color code of #b3b3b5. If you need to, adjust the text color property as well in the Property bar.

The Image Collection view is a great way to shuffle through multiple images in a folder, as shown in Figure 10-2.

the query, as shown above. The colour scheme assists in picking out the best hits. This is a form of query relaxation. It is also possible to narrow or broaden the scope of the search by re ning the query. If the result set is too large, the user can replace some classes with more speci c subclasses. If the result set does not contain the item the user is looking for, he can try to broaden the search by replacing classes with their super-classes. This principle is illustrated by the two cluster maps shown in Figure 9.7. While no single instance matches all terms of the query on the left, the right side shows that an optimal hit can be found by broadening the search to all forms of management. Note that both narrowing and broadening the scope of the query are possible due to the subclass relations in the taxonomy; therefore this capability is strongly dependent on a well-structured hierarchy. Summarizing, we can say that this visualization has transformed the query process into a browsing process.