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So far we have assumed that the number of input variables n is prede ned and xed. This is very often the case because the factors that affect the output are usually known from the prior knowledge. In many problems, however, there is a large number of (often) correlated inputs, and input variable selection (also known in classi cation literature as feature selection (Duda et al., 2000)) is a very important problem. This is especially true for inferential (intelligent) sensors (Fortuna et al., 2007; Kordon et al., 2003). This problem is usually considered in of ine mode as a part of the preprocessing and is usually approached using principal component analysis (PCA) (Li et al., 2000), GA (Smits et al., 2006), partial least squares (PLS) (Fortuna et al., 2007), and sensitivity analysis (Hastie et al., 2001). It is often dif cult to obtain representative data of dynamic and nonstationary systems that will permit extracting the best subset of input variables. Therefore, it is important to develop a method that enables automatic input variable selection on-the- y. Having such a technique, the starting fuzzy rule-based system may encompass all available inputs and can automatically trim the structure in all directions:

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the nurse could choose to use public transport, and once again, meeting points could be arranged with patients using these transportation systems. An interesting point concerns the dynamic meetings; optimization techniques and prediction models are used in order to give travel time information to both the nurse and her patient. This is like a missile and target approach, where the missile has to go to the predicted position of its target at time of impact, and not to the position of the target at current time. In our present situation, this is similar. Dynamic appointments have to reduce waiting times (hence wasted time) for both the nurse and her patient. Of course, one can choose to spend some time in the library or at the museum waiting for the nurse, but this is a parameter of the meeting that one can easily con gure. Finally, new patients could be added to the nurse s journey in the case of an emergency, even if it leads to the cancelling of a planned visit. This could be put off till the next day. Nobody is frustrated as this is the usual way it works and no one has waited for nothing.

Intelligible crosstalk presents the greatest impairment because of its distraction to the listener. Distraction is considered to be caused either by fear of loss of privacy or primarily by the user of the primary line consciously or unconsciously trying to understand

Reshaping using the Arrow tool To reshape a line or shape outline, you can drag on any point on a line using the Arrow tool. The pointer changes to indicate what type of reshaping it can perform on the line or fill. Flash adjusts the curve of the line segment to accommodate the new position of the moved point. If the repositioned point is an end point, you can lengthen or shorten the line. If the repositioned point is a corner, the line segments forming the corner remain straight as they become longer or shorter.

These dif culties generated problems and another scheme was implemented, based on the direct use of the raw measurements. We know that it is not always possible to obtain the real raw data, that is, to get rid of the various lters designed to improve the receiver solution. So, it was decided to use so-called GNSS sensors, designed to deliver a lot of data from the receiver. It is also possible to modify some parameters such as loop smoothness, constellation con guration, and many others. In fact, it was mainly the Kalman lter parameters, the code loop and the frequency loop, that were tuned. As long as one just wanted to enable the continuity of the location service between outdoors and indoors, there was no interest in

You couldn t set the background color or background image of the page. There were no tables or frames. You couldn t dictate the font. All inline images had to be GIFs; JPEGs were used for out-of-line images. And there were no forms. Every page looked pretty much the same: gray background and Times Roman font. Links were indicated in blue until you d visited them, and then they were red. Because scanners and image-manipulation software weren t as available then as they are today, the image limitation wasn t a huge problem. HTML 1.0 was only implemented in Mosaic and Lynx (a text-only browser that runs under UNIX).

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