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At first glance, the numeric format seems easier than the symbolic format. There are, however, some additional permissions that cannot be unset by using numeric notation. For example, you cannot remove the SETGID attribute on a directory by using numeric notation. You would have to explicitly remove the permission using symbolic notation. If you want to know more about SETGID and similar permissions, please check other information sources. Those topics are unfortunately beyond the scope of this introductory-level book. Meanwhile, specifying permissions with numeric notation can occasionally result in safety messages. For example, suppose that you are the owner of a file and have no permissions on the file, but you try to remove it. The Linux system will then ask whether you want to override the protection setting on the file you want to remove. If you respond yes, Linux removes the file. The same would happen if you were a member of the group. Table 6.4 summarizes the relationships between the symbolic notation and its binary notation and numeric notation counterparts. Use that table as you follow along with Example 6.3.

This system, developed by China, includes a range of vehicles from the small CZ-1D to the large CZ-2E. These launchers are available for commercial satellite services. The range of lift capabilities to the GTO vary from 200 to 3 370 kgs. This series of vehicles has plans to launch LEO satellites within a few years, where the lift capability will be greater by a factor of 2 or 3. Figure 6.41 below summarizes the characteristics of Long March launchers. g) M-Series

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localization via triangulation algorithms. These blobs can be obtained from any pixel-level map, such as color, foreground, and motion segmentation, as well as from any pixel-level data fusion. However, some dif culties arise in this procedure; in fact, most often a segmented image produces multiple connected components in place of a single component because of misclassi ed areas (missing detections) that may arise because the model does not adapt to the real imaging conditions. For example, in foreground segmentation it often happens that the target shares some color properties with the local background and thus is also classi ed as background; and motion segmentation may fail where texture is absent. For this reason, individual blobs belonging to the same targets must be clustered in some way, by paying attention to the resulting image shape and size of the resulting group. An example is provided by the minimum spanning tree, mentioned earlier in Section 4.3. 6.1.1 Localization with Three-Dimensional Triangulation

After you click the OK button, you can open the Reference dialog box again to ensure that your reference is set. You will know that your selection took effect when the Microsoft ActiveX Data Objects Library is selected in the Reference dialog box (see Figure 8-2).

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DCT-based process Source image: 8-bit samples within each component Sequential Huffman coding: 2 AC and 2 DC tables Decoders shall process scans with 1, 2, 3 and 4 components Interleaved and non-interleaved scans

Existing certificate management protocols, such as those defined by PKIX, support only a single part of the key life cycle (typically, certificate issuance). In addition, they are too complex to deal with for the lightweight Web services of today. The goal of the X-KRSS specification is to respond to this need for a complete and simpler key life cycle management protocol that focuses on applications, such as Web services, to be their clients.

Run the Castor example again to try out the manual mapping. Not much is different judging from the output. However, if you look at the order.xml file in a text viewer, you ll see that it is now clean of the metadata that Castor generates for the automated mappings. That same metadata is now explicitly coded within binding rules in the mapping.xml file. As you can see, Castor introduces a totally different way to work with XML documents. Bound Java objects are a far more natural way to work with XML. Castor is very handy for generating Java objects from existing XML data. Actually, Castor is primarily a binding tool, and it can be used to bind Java objects with other sources, most notably relational databases. The ability to map to existing XML documents is especially handy!

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