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American College of Radiology-National Electrical Manufacturers Association (ACR-NEMA), 10, 213 American College of Radiology-National Electrical Manufacturers Association standard, 26, 177 178 American College of Radiology-National Electrical Manufacturers Association standards committee, 273 274 Analog communication systems, 237 Analog echo signals, 96 Analog image receptor, 66 71 Analog-to-digital (A/D) conversion, 71 72 Analog-to-digital converters, 72, 96 Analogy-based radiographic images, converting to digital form, 67 68 Analysis of images, in CAD detecting small acute intracranial hemorrhage on brain CTs, 787 Analysis of variance (ANOVA), in bone age assessment of children, 828 Analysis workstation, 358 Analytic 3-D image reconstruction methods, 113 Analytical methods, in bone age assessment of children, 828 833 Anatomical regions of interest, 365 Anatomical structures, using frequency components to represent, 44 45 Anatomic Pathology Work ow (PWF), 289 Angle of view, in PACS implementation, 580 Angus, William M., xlii Antepartum Care Summary (APS), 291 Application design, for location tracking and veri cation system, 874 Application interface layer, 374 software modules in, 375 377 Application library layer, 374 Application middleware, with DICOM-based medical imaging informatics, 632, 633, 644 645 Application servers, 223 Application Service Provider (ASP). See also ASP entries in PACS implementation, 585 in UCLA PACS, 609, 610, 611 612 Application Service Provider backup archive, 343 general architecture of, 343 344 in UCLA PACS, 611 612 Application Service Provider model, 21, 452 CA image servers in, 495 496 for enterprise PACS, 503, 504 image/data security in, 519 setup procedures of, 346 Application services, in grid computing, 655 Application-speci c integrated circuit (ASIC) technology, with TMR, 491 Architecture. See also Software architecture of Data Grid computational services, 852 853 for DICOM RT-based ePR system, 714

Here, you can determine the colors used for the Syntax Checking. Choose the highlighting set for which you want to change a color and then click any color swatch to change the color of the highlighting set. Color preferences is also a great place to learn exactly which items are highlighted for each set.

if one is to continue the revolution in computer hardware beyond about the next decade; furthermore, nanotechnology will also allow us to fabricate an entire new generation of products that are cleaner, stronger, lighter, and more precise6 [7] Nanomaterials with structural features at the nanoscale can be found in the form of clusters, thin lms, multilayers, and nanocrystalline materials often expressed by the dimensionality of 0, 1, 2 and 3; the materials of interest include metals, amorphous and crystalline alloys, semiconductors, oxides, nitride and carbide ceramics in the form of clusters, thin lms, multilayers, and bulk nanocrystalline materials [16] All products are manufactured from atoms, however, interestingly, the properties of those products depend on how those atoms are arranged For example, by rearranging the atoms in coal (carbon), one can make diamonds.

objectives are somewhat diffuse, several solutions are good in practice The multipleperiod heuristic constructs a good solution by applying a set of sophisticated decision rules in a hierarchical way These decision rules were deducted from the hierarchical planning approach followed by the planners of the Dutch Railways Company The multiple-period heuristic applies a method of problem decomposition On the one hand, this is for practical reasons On the other hand, the decomposition method is inspired by theory, in principle by Dynamic Programming (DP) Conform the solution procedure of DP the multiple-period heuristic decomposes the shunting problem in subproblems, related to so-called planning periods Those subproblems are solved stepwise in a backward fashion From the discussion of a pure DP formulation it follows that the heuristic searches for a low-cost path in the DP-graph by evaluating a limited number of states and decisions.

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The results of the multiple-period heuristic are promising for several test cases and for a real case taken from practice To draw more de nite conclusions, one should test the heuristic on more cases from practice By its construction the heuristic is fast and exible and therefore easy to adapt and to extend during future phases in the project In future implementations of the heuristic, it might be effective to generate multiple solutions from which the planner might choose The computation time is very short (not even a second), so in future phases of the project one can evaluate more promising paths in the DP graph by extending the decision space with a second one-period heuristic based on an alternative set of decision rules Another suggestion is incorporating a route planner, which schedules the required shunts at an operational level Thus one can more accurately estimate the shunting efforts.

It should be noted that current manufacturing techniques are very rudimentary at the atomic/molecular level: casting, grinding, milling, and even lithography move atoms in bulk rather than in a choreographed or highly controlled fashion On the other hand, with nanotechnology one is able to assemble the fundamental building blocks of nature (atoms, molecules, etc), within the constraints of the laws of physics, but in ways that may not occur naturally or in ways to create some existing structure but by synthesizing it out of cheaper forms or constituent elements Nanomaterials often have properties dramatically di erent from their bulk-scale counterparts; for example, nanocrystalline copper is ve times harder than ordinary copper with its micrometer-sized crystalline structure [17] A goal of nanotechnology is to close the size gap between the smallest lithographically fabricated structures and chemically synthesized large molecules [18].

When developing further, one must keep in mind that delays and breakdowns of trains are likely to occur in practice One should pay attention to the robustness of a solution as well as to a short computation time of the algorithm In extreme cases, the Railway Company likes to rerun the heuristic quickly by inputting updated timetables Because of its speed, the multiple-period heuristic is very useful for this purpose..