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< xml version 1.0 > <!-- --> <!-- > <!--Copyright (c) 2003 Nokia. All rights reserved. --> <!-- > <!--The contents of this document are provided as is . --> <!--No warranties of any kind, either express or implied, --> <!--including, but not limited to, the implied warranties --> <!--of merchantability and tness for a particular --> <!--purpose, are made in relation to the accuracy, --> <!--reliability or contents of this document. Nokia --> <!--reserves the right to revise this document or --> <!--withdraw it at any time without prior notice. --> <!-- > <!-- --> <!-- --> <!-- > <!--Version 1.0 20 Mar 2003 --> <!-- > <!-- --> <RDF xmlns http://www.w3.org/1999/02/22-rdf-syntax-ns# xmlns:rdf http://www.w3.org/1999/02/22-rdf-syntax-ns# xmlns:prf http://www.wapforum.org/UAPROF/ccppschema20000405# > <rdf:Description ID Nokia3650 > <prf:component> <rdf:Description ID HardwarePlatform > <rdf:type resource http://www.wapforum.org/UAPROF/ ccppschema-20000405#HardwarePlatform /> <prf:ScreenSize>176 208</prf:ScreenSize> <prf:Model>Nokia3650</prf:Model> <prf:ScreenSizeChar>15 6</prf:ScreenSizeChar> <prf:ColorCapable>Yes</prf:ColorCapable> <prf:BitsPerPixel>12</prf:BitsPerPixel> <prf:TextInputCapable>Yes</prf:TextInputCapable> <prf:ImageCapable>Yes</prf:ImageCapable> <prf:Keyboard>PhoneKeypad</prf:Keyboard> <prf:NumberOfSoftKeys>2</prf:NumberOfSoftKeys> <prf:Vendor>Nokia</prf:Vendor> <prf:SoundOutputCapable>Yes</prf:SoundOutputCapable> <prf:StandardFontProportional>Yes</prf:StandardFontProportional> <prf:PixelsAspectRatio>1 1</prf:PixelsAspectRatio> <prf:OutputCharSet>

As mentioned earlier, one of the potential applications of symbolic regression via genetic programming is sensitivity analysis of nonlinear problems with a potentially large set of candidate input variables These kinds of problems are frequently encountered in the chemical processing industry Sensitivity analysis is also called the problem of input variables selection in machine learning terminology Many problems in the chemical industry are of this type Usually, there are a large number of measurements available at a plant, many of which are redundant or not relevant to the problem that one is trying to solve Engineering knowledge about the problem is usually the rst step in trying to narrow down the number of inputs Sensitivity analysis generates a ranking of all the input variables in terms of how important they are in modeling a certain unknown process.

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In linear problems the sensitivity of an input variable is related to the derivative of the output with respect to that variable In nonlinear problems, however, the derivative becomes a local property and has to be integrated over the entire input domain to qualify as sensitivity Since this approach is not really practical in a genetic programming context, the sensitivity of a given input variable can be related to its tness in the population of equations The rationale is that important input variables will be used in equations that have a relatively high tness So, the tness of input variables is related to the tness of the equations they are used in There is, however, a question with respect to credit assignment, that is, what portion of the tness goes to which variable in the equation.

Click the Edit Multiple Frames button in the Timeline. Drag the onion skin markers so that they enclose all the frames you want to select, or click Modify Onion Markers and choose Onion All.

The easiest approach is to distribute the credit (the tness of the equation) equally over all variables present Provided the population size is large enough, we can take the tness of.

The values you use vary depending upon the font size and size of the text box. Each font has different kerning characteristics, which enters into the value you end up using.

After introducing the characteristics of different media used in location estimation systems, we will describe three typical location estimation algorithms; triangulation, scene analysis, and proximity. Targeting different application environments or services, these algorithms have unique advantages and disadvantages. Hence, some hybrid systems utilize more than one type of location algorithms at the same time to get better performance. 13.4.1 Triangulation Triangulation is the technique using the geometric properties of triangles to compute the objects location. The location is estimated relative to some known framework, which consists of either xed terrestrial sites (e.g., basestations in a cellular system) or space-based satellites (i.e., the geographical positioning system). Triangulation technique has two derivations; lateration and angulation. Lateration is the technique to locate an object by measuring its distances from multiple reference positions, while angulation is the technique used to locate an object by computing angles or bearings relative to multiple reference positions. Instead of measuring the distance directly, time of arrival (TOA) or time difference of arrival (TDOA) is usually measured, and then distance is derived by multiplying the travel time and the signal velocity (3 108 m/s for light and radio). In other words, all three methods depend on emitting and receiving light or radio signals to determine the location of an object on which a light or radio transceiver is attached. 13.4.1.1 Time of Arrival (TOA) The TOA system depends on the measurements of the time of arrival of multiple signals from reference points to the object at the estimated location. As shown in Figure 13.3, in order to enable a two-dimensional calculation, TOA measurements must be made with respect to signals from at least three xed reference points. Ideally if all the time measurements are perfect without error, the intersection of

Cycloalkanes/O3 Oxidation products of sesquiterpenes Substituted cycloalkanes and related compounds / O3

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