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Life-Cycle Analysis of Recycling of Plastic Packaging Material in Germany In order to give a more speci c answer to this problem German plastics industry initiated a life-cycle analysis for all presently known routes of recycling and recovery and gained nancial support from the Association of Plastics Manufacturers in Europe (APME), Verband der Chemischen Industrie e.V. (VCI), and Duales System Deutschland GmbH (DSD). The intent was to evaluate different established routes using different technologies of plastics recycling from an environmental point of view using life-cycle analysis (LCA) (Fig. 13.16). Approximately 20 companies participated. This means they were prepared to describe their process in detail and to inform on input of resources such as energy, feedstock, and the like and on output such as airborne and waterborne emissions, solid waste, heavy metals, and other environmentally important products. A secrecy agreement assured the companies protection of any proprietary information. The German Agency on Environment participated as guest and the German TUV validated the individual data and their correct interpretation. The then present state of ISO rules on LCA was followed as closely as possible. The nal report underwent a critical assessment as requested by ISO rules. The study was awarded the Oce van der Grinten prize in 1997 and its ndings were published [8].

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Carry out some preliminary checks Hook up a monitor Attach a keyboard and fit a mouse Connect the PC to a spare electrical outlet Fire it up and see if it works! Give it a good test! This first run test is usually called a burn-in.

. . . .

a web server without your knowledge or use the your computer for a distributed denial of service attack.

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integration test would use Spring s DriverManagerDataSource and would be located in your project s /src/test/resources folder. In order to validate the test and production definition files in conjunction with a configuration for the DAO layer, you would end up with two Bean Config Sets (listed in the following table): a Config Set containing the persistence context with production configuration, and a second set containing once more the persistence context, but in this test case with a test DataSource. The files in the following table are bean definition files that are part of the sample application. Bean Config Set Name

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Subsampling to [__]: The final item in the pull-down menu is Subsampling to When Subsampling is specified, a pixel within the center of the sample area is chosen as the value applied to the sample area Thus, downsampling noted above replaces pixels from averaged color values, whereas the subsampling replaces pixels from a given color value Of the two methods, subsampling significantly reduces the amount of time to resample the image Because all that averaging is taking place with downsampling, the calculations are more extensive, thereby increasing the distillation time Subsampling, however, may result in more problems in the printed PDF file Unless you have a large singlecolor background, you are better off choosing Bicubic downsampling when printing to hard copy Compression: Acrobat Distiller has a choice for automatic compression in the Compression tab of the Job Options dialog box In Figure 5-17, note a checkbox for Compression.

If you ve made it this far through the chapter, I just want to say one thing about the Filter Factory: It s incredibly powerful and capable of doing much, much more than any filter I ve described so far. But it s also difficult to use so difficult, in fact, that it makes everything I ve discussed in the previous pages look incredibly easy and transparently obvious. The Filter Factory tests the capabilities of the most experienced Photoshop user.

Recently, ef cient planners have been developed for this class of nondeterministic domains (eg, Cimatti et al 2003; Jensen, Veloso, and Bryant, 2003) These planners represent states and perform search implicitly in a space of Boolean functions represented ef ciently with reduced Ordered Binary Decision Diagrams (OBDDs) (Bryant, 1986) The plans produced by these planners are encoded compactly with OBDDs and correspond to universal plans (Schoppers, 1987) or policies in Reinforcement Learning (Littman, 1994) Hence, a nondeterministic plan is a state-action table mapping from states to actions relevant to execute in the state in order to reach a set of goal states A plan is executed by iteratively observing the current state and applying one of the actions associated with that state In this chapter, we speci cally examine nondeterministic planning in domains where nondeterminism is caused by uncontrollable agents with speci c goals of their own.

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