2.3.5 Link budget for a regenerative transponder
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STOCKS AND COMMODITIES AS LEADING INDICATORS Stocks and commodities also qualify as leading indicators of the business cycle, although their warnings are much snorter than those of bonds. Research provided by Dr. Moore (in collaboration with Victor Zarnowitz and John P. Cullity) in the previously-cited work on "Leading Indicators for the 1990s" provides us with lead and lag times for all three sectors bonds, stocks, and commodities relative to turns in the business cycle, supporting the rotational process described in Figure 13.1. In the eight business cycles since 1948, the S&P 500 stock index led turns by an average of seven months, with a nine-month lead at peaks and five months at troughs. Commodity prices (represented by the Journal of Commerce Index) led business cycle turns by an average of six months, with an eight-month lead at peaks and two months at troughs. Several conclusions can be drawn from these numbers.
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is exact if f(x) is a polynomial.30 De ne g(x) = W(x)f(x) and vj = wj /W(xj ). We can then rewrite (14.34) as
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When we make our investments, it is the expected return along with the uncertainty in expected return that we use to gauge the appropriateness of a particular asset class or fund to a particular situation. Different investments or combinations of investments have different levels of uncertainty associated with them. Two funds might have had a similar average periodic return, for example 5%. But there is a clear difference in the two investments if Fund A had steady returns of 5% a year and Fund B had a history where half of the time the returns were 0% and the other half of the time 10%. Assuming that past history can be used as a guide to the future our projected savings would be more uncertain with Fund B. This is because Fund B has a wider dispersion of possible outcomes than Fund A. In a similar way, if our de nition of risk is risk relative to the benchmark, we expect to earn a higher return in exchange for making active decisions that change our risk relative to the benchmark. If a fund held the same securities in the benchmark in the same proportion as the benchmark, we would expect to earn the benchmark return. In this situation there is no active risk. But if instead the manager overweights attractive securities relative to the benchmark, then we would expect a higher return given the risk of these decisions not working out, leading to underperformance. In both absolute and relative risk situations, given the same average expected return, most investors would prefer the more certain to the less certain choice. So we can equate risk with the uncertainty as to the outcome of our investments. One investment is riskier than another if it has a greater dispersion of possible outcomes. In performance measurement we are interested in quantifying past performance. So how can we relate a concept of risk de ned as future uncertainty when we are actually measuring past activity This is a valid question, some would say there is no risk in past returns because these
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1. Download the Apache Axis tool kit (current release) from Unzip or untar the package to your local system directory (that is, d:\xml-axis-client) and set an environment variable as AXIS_CLIENT_HOME to its home directory. 2. To compile and test the client applications, create a run script (.bat or .sh) to ensure that the client CLASSPATH environment includes the following:
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The <Signature> element is a parent element of XML Signature. It identifies a complete XML Signature within a given context. It contains the sequence of child elements: <SignedInfo>, <SignatureValue>, <KeyInfo>, and <Object>. Also, an optional Id attribute can be applied to the <Signature> element as an identifier. This is useful in the case of multiple <Signature> instances within a single context.
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2.7.2 Decision Trees
1.5 to 5 Mbit/s 2 000 8 000 0.014
The original solution for multicast in BGP/MPLS VPNs is described in [DRAFT-ROSEN]. Although targeted to multicast traffic in a BGP/MPLS VPN setup, the solution departs from the VPN model described so far. Nevertheless, some of the elements of BGP/MPLS VPNs are reused: the multicast solution is still based on dedicated virtual PE routers (the VRF concept of BGP/MPLS VPNs) and customer traffic is still tunneled through the provider core between the PEs (the VPN tunnel concept of BGP/MPLS VPNs). Despite these high-level similarities, the multicast solution is very different from the unicast one. Exactly how different we will see in the remainder of this section. To do so, let us start by listing the requirements for handling customer multicast traffic: 1. The relevant multicast trees must be established within the customer VPNs between the sources and receivers, even when these reside in different sites of the VPN. Assuming PIM is running within the customer VPN, this means that the relevant PIM state must be communicated between the sites. 2. Multicast traffic must be forwarded over the provider s core from the source to the receivers. Figure 8.4 shows the conceptual model of traffic forwarding in a VPN. Two VPNs, VPN A and VPN B, are shown. A multicast source in site 1 of VPN A is sending traffic to receivers in sites 2 and 3 of the VPN. The traffic must be delivered from PE1 to PE2 and PE3 and from there to the appropriate CEs, CE4 and CE3. Similarly, a source in site 1 of VPN B is sending traffic to receivers in sites 2 and 3 of VPN B. The LANs in the centre of the diagram are not real, but as far as the PEs are concerned, they appear to be on a virtual LAN, and therefore a packet sourced at PE1 will reach both PE2 and PE3. Note that that this virtual LAN only connects the PEs servicing a particular VPN. Similar to the unicast case, which is based on a peer VPN model, the distribution of the PIM state between the customer sites is also based on a peer VPN model. Rather than maintaining PIM adjacencies between the customer s CE routers, CE routers only require a PIM adjacency with their local PE router. This is similar to the unicast case, where if a routing protocol is in use, the
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Terminating Processes
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As a consequence, all the protective measures used in top-secret computers will not be used, and many compromises will be made to improve response time and the ease of use. However, if one starts from the principle that, sooner or later, any system is susceptible to unexpected attacks with unanticipated consequences, it would be useful to design the system such that any possible attack will be detected. For example, by accumulating proofs that are accepted by courts, the consequences would be alleviated and the possible damages reduced. The starting point should be a correct definition of the type of expected threats and the eventual attack plans. The model has to take into account users practices and the way they will be using the system, as well as the motivations for possible attacks. Such a realistic evaluation of threats and risks permits a precise understanding of what should be protected, against whom, and for how long.
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