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:enabled rule block control make Enable block 0 ; :turn on block 0, block 20 fire block 0 on ; fire block 20 on ; :bring in data for classification rule generation message "Reading data from blackboard to generate classification rules..\n"; transfer Classdef from classes.dat ; string = "Ready to create new rules and process input data -\n" ; string + "A lot of output will scroll by - you can scroll up and view" ; string + "it in detail by selecting Cancel from any message box\, " ; string + "then entering resume\; when ready to proceed.\n" ; message "<string>"; :run block 0 run 1; :turn new rules off fire block 2 off ; :run blocks 1 and 2 message "Ready to print and fuzzify input data -\n" ; run 1 ; message "Input data after fuzzification -\n" ; run 1 ; :run blocks 3, 4 and 5 message "Preliminary classifications -\n" ; run 1 ; message "Resolving contradictory classifications -\n" ; run 3 ; :run block 7 message "Check all heart chambers present -\n" ; run 1 ; message "Getting final classifications\n" ; run ; message "ECHO.PAR finished.\n" ; exit ; :: ***************************************************** : ****************************************************** :program FUZZIFY.PAR - fuzzifies : ****************************************************** thresh 1 ;

We establish in the Comparing Monopolies with Competitive Firms section, earlier in this chapter, that a profit-maximising monopoly produces less than the socially optimal level. In particular, the profit-maximising monopoly in Figure 12-4 produces where its downward-sloping marginal revenue curve, MRm, intersects its upward-sloping marginal cost curve, MC. This output level, qm, is less than the socially optimal output level that would be produced by a competitive firm, qc. One way to get the monopoly to produce more is to subsidise its production costs so that the marginal cost curve in effect shifts down vertically. Doing so causes the marginal cost and marginal revenue curves to meet at a higher level of output. And if the subsidy is big enough, the monopoly can be induced to increase output all the way to qc. Some governments use this type of subsidy to get gas, electricity and phone companies to serve more people, especially poor people. If the monopoly firms costs of hooking up customers are subsidised, the firms are willing to hook up more customers than they would without the subsidy. Some people object to subsidising a monopoly, so this sort of solution isn t necessarily the most popular politically; but it is effective in increasing output.

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Today, the majority of data transfers within the Grid community involve large file transfer between sites using IP applications such as GridFTP. A basic all-photonic connection service that can be provided to Grid applications is the ultra-high-speed pipe for the transfer of a large amount of scientific data. For example, the current high-energy physics projects at CERN and the Stanford Linear Accelerator Center (SLAC) already generate petabytes of data. Apparently, the IP-based Internet would be extremely inefficient in this scenario. Furthermore, new latency-sensitive applications are starting to appear more frequently in the Grid community, e.g., remote visualization steering, real-time multicasting, real-time data analysis, and simulation steering. Collaborative projects analyzing the same dataset from remote instrumentation may be inclined to send raw digital data across the network via an all-photonic connection, so that processing of data can be done remotely from the data collection instrument. This will only require compatible transceivers, while the network will be completely unaware of the contents of the transmitted payload. It can be concluded that the basic optical connections, either lightpath or lighttree with different bandwidth granularities and QoS requirements, are excellent service candidates for a broad range of Grid applications.

notion of d-separation was de ned in De nition 4.1.14 on page 100. notion of a perfect map was introduced in De nition 4.1.15 on page 103.

Many new forces are reshaping the way in which banks use networks. Some of these are regulatory, such as the Sarbanes Oxley law and the Bank for International Settlements Basle II requirements. Others are changes in the nature of financial services business, owing to the fact that riskier and more profitable operations need more robust analytical capabilities to support them. In some cases, financial business is becoming more dependent on leveraged activities. This is the case when a bank s investment in a financial instrument such as a hedge depends upon a number of conditions, for instance prices of commodities and currencies. As a result, an entirely new level of accountability is required that is not possible with traditional methods. In these instances, accountants may require banks to change the way in which they evaluate risk and press for the use of more powerful and more rapid number crunching. In addition, financial institutions face declining margins on traditional operations, such as transactions for trading or investments, and one way they try to improve the profitability of these operations is to increase their volume. Many banks and brokerage houses have used more high-powered computing to scale up the number of transactions they support. But this has also required an increase in networking to support these transactions, send information about the transactions to required backup sites, and analyze the transactions for illegal activity, such as money laundering.

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