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You bid for a keyword, but what you actually pay is a different amount. Sometimes, it s very different. The actual amount you ll pay depends on your ad group s Quality Score and the bids from other advertisers. By understanding this, you can reduce the amount you pay and get more clicks for the same budget. First, let s review the formula for calculating the CPC, which is what you actually pay when someone clicks your ad. This formula includes an Ad Rank score, which is your bid multiplied by your keyword s Quality Score (QS). The CPC is your QS divided by the next-lowest ad s Ad Rank, plus 1 . Let s use an example to explain this formula. Let s say there are only three companies using AdWords in the koi market. Apricot bids $2, Berry bids $5, and Cherry bids $1. Laura clicks on all three ads. What does each company pay for these clicks The following table shows the bid, the Quality Score, the Ad Rank, and the CPC. It also explains how the ads were ranked and what the advertisers paid.

where = wave-number of interest (cm 1) = beam divergence half angle (radians) = shear given by Eq. (10.34) (cm) Parallel-face protective windows are included in SpectRx systems right after the telescope and before the output optics. The level of channel spectrum generated by such a window is calculated using Eq. (10.33) with MT = 0, and Eqs. (10.34) and (10.35). A certain degree of wedging of this window would further reduce the channel spectrum but at the cost of introducing the phenomenon of ghost images. Ghost images are generated when reflections from the wedge s surfaces (of an off-axis source, which can be many times more intense than the source of interest (on-axis)), reach the detector and give an erroneous signal. This is illustrated schematically in Fig. 10.22. Ghost images are especially destructive and must be avoided if possible.

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Spectral aliasing is the folding over of all signal and noise within the bandpass of the system into the spectral free range, which spans from 0 to the Nyquist frequency (half the sampling frequency). To avoid the overlapping of spectral features, it is important that any spectral information outside the spectral range of interest be removed. This can be done electrically with a low-pass filter, but this method does not provide a sharp cut-off over the upper limit of the frequency range or attenuation below the lower limit. A more appropriate method is to use an optical filter, which provides both a sharp cut-off and very high attenuation outside the spectral range of interest. This method also reduces photon noise.

Why They Pay That Amount Multiply the bid ($2) by the QS (QS 40) to get the Ad Rank (80). Apricot s QS (40) divided by Berry s Ad Rank (15), plus 1 means Apricot pays $0.27. Multiply the bid ($5) by the QS (QS 3) to get the Ad Rank (15). Berry s QS (3) is divided by Cherry s Ad Rank (2), plus 1 , so Berry pays $1.51. The min bid is 5 , so Cherry pays 5 .

CHAP. 2]

1. B. K. Yap, W.A.M. Blumberg, and R.E. Murphy, Applied Optics, Vol. 21, 4176 (1982). 2. J. B. Johnson, Nature 119, 50 (1927). 3. J. B. Johnson, Phys. Rev. 32, 97 (1928). 4. D. R. White et al., Metrologia, Vol. 33, pages 325 335 (1996). 5. D. D. Laporte, William L. Smith, and L.A. Sromosky, Applied Optics, Vol. 27, 3210 (1988). 6. H. Nyquist, Phys. Rev. 32, 110 (1928). 7. Hugh Lippincott, Notes on Johnson Noise, given on 19 February (2007). 8. L. B. Kish, Phys. Lett. A 352, 178 182 (2006) /physics/0509136; A Cho. Science 309, 5744, and 2148 (2005). 9. Peter R. Griffiths and James A. de Haseth, Fourier Transform Infrared Spectrometry, Wiley-Inter-science. 10. Sabrie Soloman, Sensors Handbook, McGraw-Hill Publishing Company, New York, 2009. 11. Sabrie Soloman, Sensors and Control Systems in Manufacturing, McGraw-Hill Publishing Company, New York, 2009. 12. Sabrie Soloman, Non-destructive Identification of Tablet and Tablet Dissolution by Means of Infrared Spectroscopy. U.S. Patent Number 5,679,954. 13. Sabrie Soloman, Real Time On Line Analysis of Organic Compounds for Food, Fertilizers, and Pharmaceuticals Products. U.S. Patent Number 5,900,634. 14. Sabrie Soloman, Sabrie s Index of NIR-Light Energy, Sensors Symposia, Seoul, Korea, 2007.

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