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You rst value the (slightly) wrong option by backward induction from the wrong (effective) barrier to get (almost) right numerical values for the derivative of the true option at all times on its barrier You then use these derivatives at each level of the tree in a rst-order Taylor series on the barrier to obtain modi ed barrier values for the true option Finally, you value the correct option by backward induction from the modi ed barrier 4 The following is the algorithm from an interpolation point of view:5 1 Value a target option T(S) (ie, the security the barrier option knocks into a security with zero value and that pays no rebate) and the barrier option V(S) at each node on the tree with the barrier at the effective (upper) barrier.

The computed value of V(S) on this modi ed barrier is then V(D), the value from an unenhanced computation 2 Value T(S) and V(S) with the speci ed barrier moved down to the modi ed (lower) barrier The value of V(S) on the modi ed barrier is then exactly T(D), the value of the target option it knocks into ~ 3 Replace V(D) on the lower barrier by the value V(D) obtained by interpolating between V(D) and T(D) according the speci ed (true) barrier B s distance from the effective barrier and the modi ed barrier: U B B D V (D) = T (D) V (D) + U D U D 4 Use backward induction from the modi ed barrier with V(D) as the boundary values to nd the value of V(S) at all other nodes inside the barrier Figure 6.

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3 shows the modi ed barrier algorithm interpreted as an interpolation between the upper and lower barriers There are many variations of barrier options that are traded in the marketplace, including double-barrier, double-barrier step, and delayed-barrier options..

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SAXParserFactory saxFactory = SAXParserFactory.newInstance(); javax.xml.parsers.SAXParser saxParser = saxFactory.newSAXParser();

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where Pc,w is a 3 4 projection matrix and Kc3 3 is the left 3 3 submatrix of Kc . The entire projection matrix Pc,w (or, equivalently, the intrinsic and extrinsic camera matrices), which is the goal of camera calibration, can be obtained in several ways: for example, through the direct linear transform (DLT) followed by a maximum-likelihood re nement by means of a calibration pattern and feature correspondences. We notice here that unlike the camera frame C , world and object frames have no prede ned convention, so they can be chosen according to the task of interest. For example, when tracking an object that can move onto a plane but never leave the surface, a natural choice for the x3 axis (of both world and object frames) is the plane normal direction, with origin on the plane itself, so that the object pose parameters can be given as a purely planar ( x1, x2 ) motion. 2.1.4 Uncalibrated Models

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You can test to see if it works by calling the Web service via HTTP GET:

To illustrate the method of successive substitution, also known as Picard's method, we first consider the scalar differential equation dx (B.2.2)

Reagents and Conditions: (a) i. NBS, THF-water, 0 C; ii. K2CO3, MeOH, 72%; (b) i. DHP, p-TsOH, CH2Cl2, rt; ii. O3, Py, CH2Cl2, 78 C, 61%; (c) LDA, 78 C, 30 min then aldehyde 187, 78 C $ 23 C., 61%; (d) LiClO4, C6H6, re ux, 75%; (e) i. p-TsOH, MeOH, 23 C; ii. MnO2, n-Hexane, 23 C, 71%; (f) TiCl4, Zn, THF, re ux, 42%; (g) i. KOH, EtOH-H2O, re ux, 90%; ii. LiAlH4, Et2O, 23 C, 90%; (h) Ti(OiPr)4, L-( )-DET, t-BuOOH, 20 C, 92%; (i) i. Ph3P, I2, imidazole, Py, Et2O-CH3CN (3:1), 0 C; ii. NaBH3CN, HMPA, THF, 60 C, 80%.

</StartPoint> <ViaPoint><!-- Intermediate points --></ViaPoint> <StopPoint> <Position> <gml:Point><!-- Stop position --></gml:Point> </Position> </StopPoint> </WayPointList> </RoutePlan> <RouteGeometryRequest value="true"/> </DetermineRouteRequest>

Now that we have a database, we need to be able to access it through a servlet. To do this, we need to configure a DataSource in Tomcat. There are two ways to do this, through the Tomcat Admin tool or by editing Tomcat s configuration file server.xml.

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