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UC Standardization Committee UC Standard: Test method for measuring surface contamination on silicon wafers by total re ection X-ray uorescence spectroscopy, Ultra Clean Technology, 8, 44 82 (1996) Horie, S et al Progress of ISO standardization activity on TXRF method 1: Report on RRT2 (Collecting method of surface metal) Extended Abstracts (The 48th Spring Meeting 2001), The Japan Society of Applied Physics and Related Societies, Meiji University, 2001, p 839 (31a-D-1) Mori, Y and Uemura, K Error factors in quantitative total re ection X-ray uorescence analysis X-Ray Spectrom, 28, 421 426 (1999) Hourai, M, Naridomi, T, Oka, Y, Murakami, K, Sumita, S, Fujino, N and Shiraiwa, T A method of quantitative contamination with metallic impurities of the surface of a silicon wafer Jpn J Appl Phys, 27, L2361 L2363 (1988) Kondo, H, Ryuta, J, Morita, E, Yoshimi, T.



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and Shimanuki, Y Quantitative analysis of surface contaminations.

We determine the S parameters for a cascade of nonstandard modules so we can use that cascade as an element in a cascade with standard modules having





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The GA begins, like any other optimization algorithm, by de ning the optimization variables, the cost function, and the cost. It ends like other optimization algorithms too, by testing for convergence. In between, however, this algorithm is quite different. A path through the components of the GA is shown as a owchart in Figure 2.2. Each block in this big picture overview is discussed in detail in this chapter. In the previous chapter the cost function was a surface with peaks and valleys when displayed in variable space, much like a topographic map. To nd a valley, an optimization algorithm searches for the minimum cost. To nd a peak, an optimization algorithm searches for the maximum cost. This analogy leads to the example problem of nding the highest point in Rocky Mountain National Park. A three-dimensional plot of a portion of the park (our search space) is shown in Figure 2.3, and a crude topographical map (128 128 points) with some of the highlights is shown in Figure 2.4. Locating the top of Long s Peak (14,255 ft above sea level) is the goal. Three other interesting features in the area include Storm Peak (13,326 ft), Mount Lady Washington (13,281 ft), and Chasm Lake (11,800 ft). Since there are many peaks in the area of interest, conventional optimization techniques have dif culty nding Long s

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+ m)} = 02smo,

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RFIC (RADIO FREQUENCY INTEGRATED CIRCUIT) AND SOC (SYSTEM ON CHIP)

Let s back up to understand the forces that are creating pressure on pro ts. First and foremost is the Internet. The Internet is shifting power from sellers to buyers irreversibly. Search engines and greater and faster data access are prevalent among purchasing agents. The ability for the buyer to access knowledge and information about products is unbounded. Ironically, suppliers are assisting in the shift of power to buyers. How Suppliers are providing increasingly more information about their products and services via their Web sites. As a result, the pressure on a supplier s pricing is immense. These pressures are not restricted to be between companies but they also exist among internal divisions within a company. Competition among businesses can get so blurry that business units in the same company can be customers, partners, and competitors. The inherent competition increasingly lies between different value chains selling different products. Share of wallet is displacing market share as a measure of business growth success. In short, it is the entire value chain that now requires scrutiny. To complicate matters, as products increasingly become viewed as commodities, the importance of services rises. That is, as differentiation from product advantages is reduced or neutralized, the customer relationship grows in importance. There is an unarguable shift from product-driven differentiation to service-based differentiation. Services include the manner in which goods are moved and delivered. Strategists all agree that differentiation is a key to competitive advantage. In short, the increasing desire by different types of customer segments for unique requirements is forcing suppliers to respond with increasing exibility. Of course, all of this extra effort and service comes with additional costs that can adversely impact pro ts. Another problem involves pricing. How can a supplier or retailer know on

Each eigenvector excitation produces an infinite number of Floquet modes. However, the fundamental Floquet modes that radiate along the desired direction are only TE TM produced by the eigenvector 1 . Suppose V00 and V00 are the Floquet modal voltages for the TE00 and TM00 modes, respectively, normalized with respect to the incident power at the element input. For 1 as the incident voltage vector for TE TM the subarray, the modal voltages become V00 / N and V00 / N , respectively. The factor 1/ N appears because the magnitude of incident voltage at an element the port corresponding to the eigenvector 1 is 1/ N . Further, to be consistent with

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