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If a significant proportion of the traffic is exchanged between remote earth stations, then a DAMA controlled network is the best solution. However, at the beginning of operation, a pre-assigned DAMA compatible configuration is generally sufficient. Later on, the implementation of a DAMA control should permit the traffic growth to be coped with, while keeping about the same transponder occupancy and the same number of channel units. This increase in network efficiency due to DAMA operation is illustrated by the example given below: This example shows how, in a fully SCPC meshed network, the number of satellite RF carriers (i.e. the number of SCPC half-circuits) and the number of channel units equipping each earth station can be calculated. In this example, the network includes five earth stations (A, B, C, D, E) with an assumed traffic given by Table 5.2. Using a blocking factor of 2% (grade of service: 1 in 50), the network equipment required, calculated by the Erlang Table, is given by Table 5.3. The sum of the matrix elements is 98 (98 half-circuits). Therefore 49 pre-assigned SCPC channels should be installed for a PAMA network. If a DAMA system is implemented at a later stage, the Erlang Table shows that the traffic capacity of these 49 two-directional channels will be 39.3 Erlang, whereas the PAMA network enables a traffic of 15 Erlang (sum of the elements in Table 5.2). Therefore the subsequent implementation of DAMA will: increase the traffic capacity by a factor more than two, with the same equipment; give full flexibility for the distribution of the traffic.

Figure 2.36 Distributions of heights of singers. A multipanel display of histograms where each panel shows the distribution of the heights of the singers in each section of bass, tenor, alto, and soprano

14

4.2 4.2.1

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QoS-Frame(T) with QoS control QoS-Frame(D) with QoS control QoS-Frame(T) without QoS control QoS-Frame(D) without QoS control 1 2 3 4 5 6 7 8 9 10

is, to remove directories and their contents recursively. Removal in this manner does not require the directories to be empty before execution.

(4.120)

market plunge. At such times the interplay between the stock market, interest rates, and the dollar is immediate and dramatic. Rising interest rates eventually began to pull the dollar higher in 1988 (after the stock market had stabilized). Soaring short-term rates provided a bullish backdrop for the dollar rally. By April of 1989, short-term rates had peaked (see Figure 6.2). Within two months the dollar started to weaken as a result. Figure 6.3 compares dollar trends to 30-year Treasury bond yields. While bond swings aren't as dramatic as the T-bill market, the relationship to the dollar is basically the same. The bond market, being a long-term investment, is more sensitive to inflationary expectations as lenders demand a higher return to protect their investment from the ravages of inflation. Bond yields turned higher in 1987 as the inflationary implications of the falling dollar (and higher commodity prices) began to take hold. The collapse in the dollar during the fourth quarter of 1987 was the direct result of the plunge in interest rates resulting from the October stock market crash. The dol-

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with uniform scale, rotation, and translation, and deduce its subcases later. Omitting the n index, the LSE solution in terms of ( s, R, t) has been given by Umeyama [156] and consists of the following computations: Mean vectors: y = (1 N )

(2.14)

Car[0] Car[1] Car[2] Car[3] Car[4] = = = = = "Ford"; "Toyota"; "Volkswagen"; "Mercedes"; "Honda";

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=TYPE(A1)

where 1,2 is the year fraction between T1 and T2, and is assumed to be the same in both the domestic and foreign markets. Given the future times T1 and T2, we can compute the value of a quanto caplet that pays off at time T2, 1,2Nmax(Ff(T1; T1, T2) K, 0) in domestic currency (14.28)

The root element (which is always the top-most element in an XML document) serves as the container for all the contents within the document. Every XML document must have one (and only one) root element. The MyTable element

15

The contribution to value added made by a particular security holding is an important performance measurement metric. It allows us to dissect the relative performance of a fund and its benchmark. Let s take a closer look at what makes up the contribution to value added. In Exhibit 17.6 the contribution for Security D is 2% for the fund and 2.5% for the benchmark. The contribution to relative return for Security D was 0.125%. We can dissect this relative value added into two pieces; one being the value added to the fund by investing in this security as opposed

=INDIRECT( $A$1 )