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When an unexpected error occurs in the program, the Python interpreter creates an object of the appropriate exception class. As discussed earlier, this is the first phase where, after creating the object, the Python interpreter passes it to the program by throwing the exception. The exception object contains the information about the type of the error and the state of the object when the exception occurred. Then, you can write the code to handle the exception using an exception handler. Various exception handling techniques can be used to trap an exception and then give instructions to the interpreter based on the exception that occurs.

specifications, thus enabling interoperability with those compliant applications. Some of the key design requirements of the Web services architecture are the following:

P0 *

2

The output of the run should be similar to the one shown in Figure 12.20. The previous steps will install the necessary JAR files in the JWSDP environment as well as create database tables and populate some of the tables with necessary data. The services also require that java.sql.DataSource is registered so that the clients can look the DataSource up using JNDI API. To register the DataSource, open the Admin tool (http://youhost:8080/amin) and configure the data source with the following parameters:

Two types of interregister signalling may be suitable: the decadic signalling and the multifrequency signalling.

The Black-Scholes prices can be found by solving the Black-Scholes PDE by transforming the problem via a change of variables and then solving the resulting transformed problem by a piecewise quadratic nite-element method in space and Crank-Nicolson nite-difference method in time. See Jackson, S li, and Howison (1999) for details.

(4.143)

7.8.1.1.3 Mechanical equipment (heating, ventilating and air-conditioning: HVAC)

Identify and echo the current shell s PID. Ask script1, as it is being executed, to echo back the PID of the shell in which it is actually being executed.

i =1

An array is a group of elements of the same type that have a common name; you refer to a specific element in the array by using the array name and an index number. For example, you may define an array of 12 string variables so that each variable corresponds to the name of a different month. If you name the array

This logic system is fed with the following inputs: the control commands; the alarms from the various amplifier circuits.

15 16

std::vector<boost::shared ptr<core::State> > initStates; so that the uniform sample bounding box, speci ed above, will be centered around this state. Now, to track the object, we simply call in the main camera loop the methods particle.predict(targetVec); pColHisto->preProcess(srcImage, preProcessROIs); particle.correct(targetVec); where the preProcess method should be called after prediction if the ROIs predicted are going to be used. The correct() step will compute the particle weights by calling the Likelihood function implicitModel for each hypothesis, then estimate the output average and covariance matrix. The resampling step will be done instead by the predict() function before drifting the particles. We notice here that preProcess is the only method that should be called from the original Modality template pColHisto, and not from the Tracker or Likelihood classes. This is meant for ef ciency reasons, especially in multithreading, since multiple modality trees may share the same preprocessed data, which should be obtained only once. Therefore, the preprocessed data are always stored into static variables and computed by calling the method from the base modality, which has been cloned in the tree instances. Afterward, we can display the output of our tracker by taking the internal output state of the respective target: targetVec[0]->outputState() that corresponds to the weighted average of the particle states for target 0. The function that provides visualization of our model is output::Output::drawPose, as described in Section 7.2.4. Figure 7.7 is a snapshot of the object de ned previously, tracked in real time with the color-based particle lter. For debugging purposes we can also draw the entire particle set by calling the same function on each particle p state particle.getParticles(p). 7.2.6 Tracking Multiple Targets

Figure 13.4 DG applied for contingency capacity support: a support for both feeders; b support for only one feeder.

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To check the status of any queue that is not the default queue (assuming again that lp1 is the alternate printer):

{=IF(n=0,0,SUM(IF(MOD(TRANSPOSE(ROW(INDIRECT( 1: &COUNT(Data))))1,n)=0,Data, )))}

This formula returns a text string that describes the compounding frequency entered into cell B7. All of the other cells in the user input section contain values.

Figure 1-17: The steps in this wizard are nearly identical to those of the Import Spreadsheet Wizard.

And for the EJB:

B ( p, q) = cos ( p , q ) =