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Wind speed u0 nacelle height above ground z, height anemometer mast h Reservoir height Hs , wave period T P / HQ P / R2 A P / T 2

Installing the demo version . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 775 Uninstalling Sound-Proof . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 776

statistics and optimize the pose. However, a color-space conversion can also be performed if it is statistically more convenient for the classi cation likelihood. Sampling model features consists, as already mentioned, of collecting a uniform set of contour points and normals in the image. We notice that if data fusion is carried out using the contour points modality, the sampling procedure can be performed only once since the two classes will share the same reprojected points. Feature-level matching involves the following substeps: 1. Collect color pixels along the normal to each contour point, on both sides. 2. Compute the online local statistics from these data.3 3. For the same pixels, compute the assignment errors, which are measurement residuals, to the respective side of the curve, as well as their Jacobians and covariance matrices. Hereafter, we consider these three steps in more detail. In the original formulation [74], statistics were collected from weighted areas around each contour point, on either side (Fig. 4.44 left). To simplify the computation, as also suggested by Hanek and Beetz [74], we can rst sample points along the respective normals, separately collect statistics, and afterward blur each one with its neighbors (Fig. 4.45). This is fully equivalent to the initial procedure, but computationally more convenient. From each contour position y i, J foreground and background color pixels are collected along the normals n i up to a distance L, and second-order moments are estimated for the foreground and background sides (F and B), respectively):

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Summary

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Add97: Res 126 & 726 Add97: Res 126 & 726

RSVP requires a periodic exchange of messages once an LSP is established in order to maintain ( refresh ) its state This can be achieved by periodically sending Path and Resv messages for each active LSP If a router does not receive a certain number of consecutive Path or Resv messages for a particular LSP, it regards the LSP as no longer required and removes all states (such as forwarding entries and bandwidth reservations) pertaining to that LSP The processing overhead of such a scheme can become a scaling concern for a router maintaining a very large number of LSPs In order to address this, the Refresh Reduction Extensions to RSVP were devised to reduce this overhead These include a Summary Refresh Extension that allows multiple RSVP sessions (and hence multiple LSPs) to have their state refreshed by a single message sent between RSVP neighbors for refresh interval [RFC2961].

PROCESS IMPROVEMENTS The productivity of a single worker today is vastly superior when compared to a similar individual of equal capability10 years ago, and 10 years prior to that. This productivity is attributable to information technology and to those who rely and depend on IT to satisfy ever-increasing complex business processes and relationships.1 At the macro-U.S. level, economists broadly agree that economic productivity gains that surged around 1995 through 2003 at 3.90 percent were largely attributable to technology: the development of new industries, the acquisition of hardware/software, and the services that are attached to these products, which are higher than periods prior to 1995 according to publications by the Federal Reserve Banks.2 The period following the post-2003 resurgence is at a macroeconomic scale trending downward, which implies that the U.S. general economy is receiving a decrease in gains from the technology industry.3 A diverging set of hypotheses on the macroeffects are too tangential to the topic of this book to discuss, on the economy after the massive buildup within corporations, but a consensus is beginning to emerge on the gains within companies. Technology has contributed efficiency gains in productivity, as indicated by the growth through the mid-1990s. The projected harder times after 2000 resulted in companies purchasing less technology and focusing more on streamlining their

After the command executes, all Perez sees is another shell prompt, because all results will be in list.file. Meanwhile, the file descriptor table for this example is shown in Table 7.11.

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