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Figure 9-12. Transformation matrix to translate ten units to the right In general, the result of multiplying a point (technically a vector) by the matrix is (x * M11 + y * M12 + offsetX), (x * M21 + y * M22 + offsetY). There is a special matrix, known as the identity matrix, where M11 = 1, M12 = 0, M21 = 0, and M22 = 1, and OffsetX and OffsetY are 0. If you multiply any (x,y) point by the identity matrix, you ll get the same point again, provided that OffsetX and OffsetY are 0. (Go ahead and try this on a piece of paper.) This identity matrix is important because it is the default configuration of the matrix. We can skew both coordinates and translate the element at the same time by specifying OffsetX and the M12 and M21 properties as follows: <Rectangle Stroke="Crimson" Fill="Crimson" Width="50" Height="50"> <Rectangle.RenderTransform> <MatrixTransform> <MatrixTransform.Matrix> <Matrix OffsetX="-10" M12="0.5" M21="0.5"/> </MatrixTransform.Matrix> </MatrixTransform> </Rectangle.RenderTransform> </Rectangle> From left to right, Figure 9-13 shows our normal rectangle, the rectangle translated right using a matrix, and the rectangle skewed and translated at the same time.



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split into two networks One half, still called ARPANET, continued to be used to interconnect research and academic sites; the other, called MILNET, was specifically used to carry military traffic and ultimately became part of the Defense Data Network That year was also a good year for TCP/IP It was included as part of the communications kernel for the University of California s UNIX implementation, known as 42BSD (Berkeley Software Distribution) UNIX Extension of the original ARPANET continued In 1986, the National Science Foundation (NSF) built a backbone network to interconnect four NSF supercomputing centers and the National Center for Atmospheric Research This network, known as NSFNET, was originally intended to serve as a backbone for other networks, not as a stand-alone interconnection mechanism Additionally, the NSF s Appropriate Use Policy limited transported traffic to noncommercial traffic only.





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exit trades using the modified standard exit signal exit z 0) ( I entryprice = entryprice + pt1im - mstp * exitatrLcb1; * exitatr[cbl ;

NSFNET continued to expand, and eventually became what we know today as the Internet And while the original NSFNET applications were multiprotocol implementations, TCP/IP was used for overall interconnectivity In 1994, a structure was put in place to reduce the NSF s overall role in the Internet The new structure consists of three principal components The first of these was a small number of network access points (NAPs), where ISPs would interconnect to the Internet backbone The NSF originally funded four NAPs in Chicago (operated by Ameritech, now part of SBC), New York (really Pensauken, NJ, operated by Sprint), San Francisco (operated by Pacific Bell, now part of SBC), and Washington, DC (MAE-East, operated by MFS, now a division of MCI) The second component was the very High-Speed Backbone Network Service, a network that interconnected the NAPs and was operated by MCI.

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It was installed in 1995 and originally operated at OC-3 (15552 Mbps) but was upgraded to OC-12 (62208 Mbps) in 1997 The third component was the routing arbiter, designed to ensure that appropriate routing protocols for the Internet were available and properly deployed ISPs were given 5 years of diminishing funding to become commercially self-sustaining The funding ended in 1998, and starting at roughly the same time, a significant number of additional NAPs have been launched As a matter of control and management, three tiers of ISPs have been identified Tier 1 refers to national ISPs that have a national presence and connect to at least three of the original four NAPs National ISPs include AT&T, Cable & Wireless, MCI, and Sprint Tier 2 refers to regional ISPs, which primarily have a regional presence and connect to.

Table 12-I furnishes some of the performance data for the top 20 solutions for long entries at the open (GFile 1). Each line represents a different trading model. The parameters are not shown, but the line or generation number (LINE), the probability or statistical significance (PROB, the decimal point is omitted but implied in the formatting of these numbers), the average dollars-per-trade ($TRD), the total number of trades taken (TRDS), the profit factor (PFAC ), the annualized return-on-account (%ROA), and the net profit or loss (NET) in raw numbers are provided.

While you could use the MatrixTransform class to combine multiple transformations into a single transformation, if you want to combine two or more of the directly supported transformations (such as a rotation and a scale), you can use the TransformGroup transform. Figure 9-14 shows the result of combining a ScaleTransform and a RotateTransform together inside a TransformGroup.

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The performance of most of these models is nothing short of impressive. The better models are statistically significant beyond the 0.00007 level, which means these solutions have a very high probability of being real and holding up in the future. Many of the returns were greater than 50% annualized. In some cases, they reached much higher levels. While the limit order had many of the best solutions, all orders had many good, if not great, solutions. As in OUT earlier study, the GA succeeded admirably in finding many tradable models.

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