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A transaction can be defined as a group of one or more database operations. Almost all databases perform transactions during updates. As a result, sets of database operations are performed as a single unit. During transaction processing, a lock is obtained that prevents other scripts from interfering with the progress of the transaction. The database object of LiveWire supports transaction processing. A transaction is initiated by invoking the beginTransaction() method. The changes and proceedings of a transaction are saved and closed using the commitTransaction() method. In addition, you can use the rollBackTransaction() method to undo a transaction before it is committed. The following code illustrates the use of transaction processing to add a new customer record to the Customer table: 349

Session Initiation (SIP)

This suggests a uctuation in changes in the slope of the yield curve over time. The second component is called the tilt component and 1.43 percent of the total variation is attributed to it. The factor weights of the third principal component are almost all positive for the short-term rates and negative for the longer-term rates. This component in uences the convexity of the yield curve, and 0.65 percent of the variation during the data period is attributable to changes in convexity.

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C = {( y1, y2 ) : ( y1, y2 ) = 0}, so that its temporal evolution is obtained by considering as a function of time, Ct = {( y1, y2 ) : ( y1, y2 , t ) = 0} . Figure 4.25 illustrates this idea; we can also see that if the topology of the curve changes (e.g., by splitting), this is handled much more easily by moving the function in space rather than moving and re-parametrizing the contour. The main difference between the two approaches can also be related to Fig. 3.4. The snakes algorithm is a Lagrangian approach, where control points on the contour are tracked from frame to frame, whereas level sets are a Eulerian approach, which recomputes the entire function pixel-wise, afterward localizing the contour as a by-product given by the pixels where = 0, whereas the blob is de ned by > 0 (or < 0). To formulate the problem, we rst reconsider the evolution of a contour Ct in the variational framework of snakes: C E ( C ) = = vn t C (4.56)

7.2.2.2.3 Polarizer operation i) Circular polarization (CP)

We can gain insight into the degree of association between two variables by plotting the observations. A graph plotting the periodic fund-benchmark return pairs allows us to visualize the relationship between the fund and benchmark returns. Exhibit 11.7 is a scatter diagram plotting the relationship between the fund and benchmark returns. Each marker represents one monthly return. Its distance from the vertical or Y-axis, measured along the horizontal scale, represents the benchmark return. The distance of the marker from the horizontal or Xaxis, measured on the vertical axis in the middle, represents the fund return. The arrangement of the plotted returns on the chart shows that there is a strong correlation between the two sets of returns. Most of the return pairs are located in the top right and bottom left quadrants of the chart. This dispersion occurred because when we had high benchmark returns, we also had high fund returns, and vice versa. The scatterplot is a visual indicator of the high degree of fund and benchmark return correlation. If the returns were less correlated, the scatterplot would show more returns in the other two quadrants. Assuming that the fund is comprised of holdings selected from an underlying universe represented by the benchmark, we expect a high degree of correlation between the fund and benchmark returns. To identify the degree to which the fund returns vary given the variability in the benchmark returns we can calculate a statistic called Beta. Beta isolates the degree of benchmark, or market-related risk inherent in the fund,

Introducing Arrays . . . . . . . . . . . . . . . . . . . . . . . 375 Performing Magic with Array Formulas . . . . . . . . 397

FIGURE 8.10 An example of high capacity earth station with TDMA-TDM-PSK and DCME: equipment configuration

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