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= (1 - x1)Qn - x2Q21 - (1 - x1)Q12 + x2Q22 = *2(Qn + Q22 ~ Qn ~ Q21) = x2(Qn + Q22-2Q12) (D.I.12)

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Children follow a series of Binking Togetherlessons. Aims for group talk are made explicit in the whole class introduction. During plenary sessions, groups reflect on the quality of their talk. In these lessons, the class are directly taught speaking and listening skills (such as challenging with respect, reasoning, negotiating ideas) and are provided with contexts for collaboration in which they can apply such skills. Classes create and agree on a shared set of ground rules for exploratory talk to use when working with one another in groups.





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we learned in step 2, to map from object to camera space, we also need the Warp class and a SensorModel; this is done in the usual way Next we declare the color-based modality ColourHist2D * pColHisto = new modalities::ColourHist2D(warp, camIdx) where the camera number camIdx must be speci ed, since for multicamera systems we have a modality instance for each camera Before using this class, we need to set some parameters; since each modality may have many parameters for its processing functions, of very different type and semantics, we introduce an abstract class core::util::ParameterContainer, from which any modality also inherits In general, we also distinguish between online and off-line parameters, where the former are allowed to change during processing, while modifying the latter forces the program to do a reinitialization of the modality.

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Schrader B, Mcicr W ( 1975) Fresenius Z Anal Chem 275:177 Schrader B, Meier W, Gottlieb K, Agatha H BarentLen H Bleckinann P (1971) Ber Bunsenges Phys Chein 75:1263 Schradcr B, Meier W, Steigner E, Zolirer F (1971) Frescnius Z Anal Chcm 254:257 Schrader B, Nerdcl F, KresLe G ( 1959) Z Anal Chein I70:43 Schrader B, Nerdel F, Kresze G (1960) Naturwiss 47: 198 Schrader B, Niggemann W, Belz HH, Schallert B (1981) Z Chem (Leipzig) 21:249 Schrader B, Simon A (1988) Microchim Acta 2:227 Schradcr B, Spiekermann M Hccht L Bougeard D (1984) J Mol Struct 1 I3:49 Schrader B, Stcigner E (1970) Liebigs Ann Chcm 735:6 Schrader B, Steigner E (1971) Fresenius Z Anal Chem 254: 177 Schrader B Stcigner E (1973) chapt 9, Raman Spectroscopy of Steroids In: Hoffman E (ed) Modern Methods of Steroid Analysic.

5-norbornene-2-carboxylic acid or 5-norbornene-2-methanol, with many di erent arene complexes containing hydroxyl or carboxylic acid functions.119 122

Academic Press, New York Schrader B, Tischer M, Podschadlowski R, Schlcmmer H ( 1988) Eleventh International Conference on Raman Spectroscopy, John Wiley & Sons, London, p 957 Schroder G ( 1987) Technische Optik Vogel Buchverlag, Wiirzburg Schrodinger E (1926) Ann Phys 81:109 Schrotter HW (1982) In: Kiel'er W, Long DA (eds) Non-linear Raman Spectroscopy and its Chcmical Applications D Reidel, Dordrecht, p 143 Schrotter HW (1982) Linear Raman Spectroscopy: A State of the Art Report In: Kiefer W, Long DA (eds) Non-Linear Raman Spectroscopy and its Chemical Applications, Reidel, Dordrecht, P3 Schrotter HW Berger H, Boquillon JP, Lavorel B, Millot G (1988) High-Resolution Nonlinear Raman Spectroscopy of Rovibrational Bands in Gases In: Salzer R, Kriegsmann H, Werner G (cds) Progress i n Molecular Spectroscopy, Teubner Texte zur Physik, Bd 20.

For color histograms, we have the following relevant feature-matching parameters: ColourFormat preProcess_DestColorFormat: output color space for the preprocessing step, in our case cvdata::Image::HSV int sampleModelFeatures_Bins1/2/3: number of bins for each histogram channel double matchFeatVariance: the variance R 2 for the feature-level likelihood bool matchFeatWithMdetect: a ag, specifying whether to match the off-line reference histogram (after features sampling) bool matchFeatWithMtrack: whether also to match the online reference histogram (after features update) double matchFeatMtrackWeight: weight for the online histogram distance double matchFeatMdetectWeight: weight for the off-line histogram distance Modality::MeasComputeFlags: common ags to all modalities, de ning which data are going to be stored in the measurement structure The last parameter speci es which of the ve elds of measurement data [eq 31] are needed by the subsequent module in the pipeline.

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