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Signal -9 (also known as KILL in the tcsh shell or SIGKILL in the bash shell) cannot be caught or ignored, so it terminates a process at the point of execution not allowing for a graceful shutdown of the process Use -9 with caution 9 (1) The job will not lock up the user s terminal while it is running (2) If the user wants to or has to log out of the system, the job continues running Upon the user s return, the status of the job can be checked 10 They are called daemons They are usually started when the system is started and stop only when the system shuts down 11 False The user is always in the original directory if the command was started in the normal fashion (that is, without using the dot [ ] command).

import Threading class MyThread(Threading.Thread):

On the other hand, PE4, not having any active multicast receivers in its domain, is not an egress point of the P2MP LSP and so does not receive any unnecessary traffic A variation on this scheme is to use a separate P2MP LSP for each multicast group, to avoid the situation where PEs receive unnecessary traffic at the expense of requiring more P2MP LSPs in the core In this case, PE3 would be an egress point on two P2MP LSPs, one corresponding to G1 and the other to G2 Likewise, PE2 would an egress point on two P2MP LSPs, one corresponding to G2 and the other to G3..

As we have seen, the goal of image segmentation is to identify connected regions that most probably belong to a single object or to a physically distinguishable part of an object, because they show relatively uniform visual properties such as uniform color, texture, or motion eld. In particular, the output of image segmentation is a binary or n-ary classi cation that assigns a given pixel to the objects of interest or to the background, possibly based on prior models of the object and/or the background. This map can be re ned through morphological operations such as erosion or dilation, used to remove noise, and nally, to detect clusters of connected pixels, or blobs. Figure 4.17 shows the result of blob detection on a foreground map, followed by further blob grouping that connects blobs belonging to the same target, in this case a human silhouette, on the basis of prior shape attributes such as the expected size and height of the region.2 A general blob-based target detector is described in more detail in Section 6.1; here we concentrate more on feature description and a matching procedure. Blobs that have been detected can be matched to the model silhouette expected at the pose predicted by de ning suitable shape descriptors and the likelihood function with single or multiple association hypotheses. In the

Because the command executes in a subshell, any environment changes made in the subshell are not passed back to the parent process..

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