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Key stakeholders are the main players in the project, holding high power to in uence the project and high level of interest in it. Main players are more likely than any other stakeholders to create dif culties in solving con icts if their needs are not attended. Keepinformed stakeholders have great interest in the project (land owners, nearby residents, public in general, groups of interests, environmental bodies) and may be severe opponents to it but have limited power to in uence project decisions. Keep-satis ed stakeholders, on the contrary, hold high power to in uence the project decisions (investors, authorities, legislative bodies, investors, media), but are often passive, meaning that con icts with them may be avoided if they feel happy with the implementation of the project. The last set of stakeholders is the minimal effort group, who have low interest in the project, therefore raising few con icts, and are not able to have a great impact on the decisions (trade and industry, for instance). It is worth noting however that the examples given above between brackets correspond to typical stakeholder positions in mainstream construction projects

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Crop: The Crop tool in Camera Raw is fairly straightforward. Just select it and drag around the area you want to crop. If you want to straighten as well, just use the rotating arrow that appears when you hover over one of the corners and rotate the cropped area. Double-click to finish. One difference you ll note about cropping in Camera Raw is that even cropping is a non-destructive edit. Even after opening and closing the image and creating numerous other settings, you can click the Crop tool to display the entire image and reset the crop boundaries, as shown in Figure 8.3. Straighten: Use this tool to straighten a photo. Drag it in what should be a straight line in your photo, and your image rotates to compensate. This tool is also non-destructive; you can correct the results at any time.

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In this chapter, you find out how to repair a range of image problems that arise from various kinds of wear and tear. Repairs include reenergizing faded images, removing noise and compression damage, removing dust and scratches, zapping blemishes, and making anyone look years younger (in a Photoshop image, anyway).

Large-scale development, Full definition of interfaces, plus detailed eventually with detached test cases as acceptance tests. teams, but all working within the same architectures and targeting completeness and correctness . Definition of the external specification of a component that will be used by another team to assemble an integrated system. The industry-level development specification plus detailed specification of interface semantics and possible inclusion of certain detailed internal specifications .

If you are working in an enterprise, you might have access to additional facilities through Groove Server or SharePoint Server. Because implementation can vary substantially, it would be impossible for this chapter to accurately or adequately describe how you interact with the environment created by your IT department. Instead, this section focuses on the individual user s Groove workspace experience, and aspects common to all users of the SharePoint Workspace 2010 client application with respect to Groove workspaces. n

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You can convert a freehand line into a points curve by clicking the points curve button. This is helpful if you need to make some additional adjustments to the points curve after you change it using the Freehand tool. n

Creating custom actions is covered in 5. You can refer to that chapter for information necessary to build the actions and action sets that can be utilized by the Batch and Droplet processing tools. n

Pseudorandom Memory Search Example Pseudorandom shift register counters are standard logical devices. Figure 4-12 shows how a small search for the image of a ladybug could be implemented using a pseudorandom counter. Shown is a shift register counter that, to begin, is initialized to all 1 s. Initially, none of the cues are masked (blocked) and the count begins in this model with a count of 1111, and this basically refreshes the current image in short-term memory. Soon after, the count jumps to 0111. This takes the feature red away. Now the cues are x3, little black spots. Brain memory might pop forth a dalmatian, a type of dog, or a leopard, a cat with spots. These images are subliminal at this point. What has happened is that spots are now associated with a dalmatian, a creature with spots, or a leopard. However, cats and dogs do not match many of the available cues, so their importance is low. They are not the sought-after image and thus do not enter short-term memory. When there are hundreds of features, a pseudorandom search will tend to change only a few features at each step; so usually, one does not expect a radical change of subject, although it could happen. As the pseudorandom count proceeds, a variety of different recalls ash into short-term memory at a rate of several per second, as fast as memory can work.

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