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Figure 19.4-3. Parameters in facilities directive messages. (From IS-41.5-B. Reproduced with permission of TIA.)
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The default setting is for the Shutter button to adjust the focus. By pressing the button halfway down, the auto focus is activated and locked. You can turn this function off, and in that case, the multi-selector s center button acts to adjust and lock the focus. When this is set to Off, the shutter can be released even if focus has not been achieved.
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Our estimates t and V, defined through (8.38) and (8.39) with the help of averages over the sample distribution, clearly can be regarded as functionals t(F)and V ( F ) of some underlying distribution F . The estimates are vector- and matrix-valued; the influence functions, measuring changes o f t and V under infinitesimal changes of F , clearly are vector- and matrix-valued too. Without loss of generality, we can choose the coordinate system such that t ( F ) = 0 and V ( F ) = I . We assume that F is (at least) centrosymmetric. In order to find the influence functions, we have to insert F, = (1- s)F+sG, into the defining equations and take the derivative with respect to s at s = 0; we denote it by a superscript dot.
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We have relied on a widely used commercial tool 3 for the creation of mind maps. It supports collaborative engineering of mind maps through peer-to-peer communication and has advanced facilities for graphical presentations of hierarchical structures, for example, easy to use copy and paste functionalities and different highlighting mechanisms. Its strength but also its weakness lies in the intuitive user interface and the simple but effective usability, which allows for quick creation of mind maps but it lacks expressiveness for advanced ontology modelling. By nature, mind maps have no assumptions for its semantics, that is, elements connected by branches are somehow associatively related to each other. This assumption ts perfectly well during the early stages of ontology development for quick and effective capturing of relevant knowledge pieces and makes the mind map tool a valuable add-on. Mind2Onto integrates the mind map tool into the ontology engineering
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Think of it as a function call; the stuff inside the brackets is an argument to that function, and the function returns either true or false. So, in the first case, you ask if whether the value of op is + (the == symbol is an equality comparison). If so, then the code between the braces is executed, and the values are added. If not, the code moves on to the next statement. This continues until it either executes one of the blocks or runs through the complete if statement and does nothing. Save your file and then reload the browser. Try it with different operations. There s quite a lot that still has to be done here. For example, someone could enter decimal numbers as terms and really mess things up. Or you could type the letter P instead of a mathematical operator, giving more undesirable results. As you ll learn, there are certain validations that need to be done to turn a proof of concept into a real-world application. But here s your introduction. Now let s take a look at some of the building blocks of JavaScript.
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WordWrap (Public Instance Property)
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FIGURE 19.5 A Smart Component with auto-sizing
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You can t argue with its compactness, and it s definitely expressive; you can readily see what this code does. But I find that I don t use switch very often, perhaps owing to its syntax being different from PHP code. It simply looks out of place in my code, so I m less inclined to use it. There s one more format that if else comes in: the ternary format (ternary means three parts: the condition, the true statements, and the false statements). It s an extremely brief format and, like the switch statement, it feels a little out of place. But occasionally within my HTML code, I find this format very attractive:
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114 Part II Creating Great Photos with the Sony Alpha A700
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Based on design experience, a ow chart of LNA design procedures is shown in Figure 1.21. It should be noted that
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Misadjustment: the size of deviation of the converged state of the iterative algorithm from the exact MSE solution. Computational effort per iteration. In the following, we discuss two algorithms that are widely used the Least Mean Square (LMS) and the Recursive Least Square (RLS). Least Mean Square Algorithm The LMS algorithm; also known as the stochastic gradient method , consists of the following steps: 1. Initialize the weights with values e0 . 2. With this value, compute an approximation for the gradient of the MSE. The true gradient cannot be computed, because it is an expected value. Rather, we are using an estimate for R and p namely, their instantaneous realizations: Rn = u uT n n pn = u cn n where subscript n indexes the iterations. The gradient is estimated as n = 2pn + 2Rn en (16.27) (16.25) (16.26)
2. Next, RMB click the sketch in the graphics window and click Select Chain. This selects any non-construction, end-to-end sketch entities. Click Offset Entities on the Sketch toolbar. Offset to the inside by .400 inches. Apply .500-inch sketch fillets to each of the corners. 3. Click Extruded Cut on the Feature toolbar. By default, the extruded cut will cut away everything inside the closed profile of the sketch. Look down the FeatureManager window and click the check box on the top bar of the Thin Feature panel. Make the cut Blind, .100 inch. The Thin Feature type should be set to Mid Plane with a width of .400 inches. The PropertyManager and graphics window should look like Figure 4.6.
Change Control and Workplace Management
Basic Idea Underlying Multiuser Detection Multiuser detection is based on the idea of detecting interference, and exploiting the resulting knowledge to mitigate its effect on the desired signal. Up to 1986, it had been an established belief that interference from other users cannot be mitigated, and that in the best case, interference behaves like AWGN. Correct detection and demodulation in the presence of strong interference was thus considered impossible, just as it is impossible to correctly detect signals in strong noise. The work of Poor, Verdu and others summarized in Verdu [1998] demonstrated that it is actually possible to exploit the structure of multiuser interference to combat its effect. Using such a strategy, interference is less detrimental than Gaussian noise. Multiuser detection was intensely researched during the 1990s, and the rst practical systems using this approach were introduced in the subsequent decade. The conceptually simplest version of multiuser detection is serial interference cancellation. Consider a system where a (single) interfering signal is much stronger than the desired signal. The receiver rst detects and demodulates this strongest signal. This signal has a good SINR, and can
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