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7: Fighting Recessions with Monetary and Fiscal Policy
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Trade is about trust, not security. People will deal with others, or not, on the basis of belief, not objective technicalities, and in the arena of trade they deal on the basis of trust. Trust is essentially subjective; it may be backed up by processes that objectively deserve that trust, but the subjective dominates. Trust will not necessarily be unconditional; every day of our trading lives we accept a degree of risk that the other party will not play entirely fair. We do so on the basis that, on balance, we shall bene t more than we suffer. Of course, the various measures that, collectively, are described under the term security are intended to realise this trust, but they are enablers, not ends in themselves. This is probably wise: it may be better to rely on the gut-feel of many customers than on the considered opinion of a single security of cer; there is no better audit of the integrity of a system than barrage testing by external parties. Moreover, there is another reason why we should not too readily use the term security in the domain of eBusiness: it is too much tied up with military security. Certainly the basic techniques, the algorithms, are the same, but the outlook, the security processes, are often a long way apart. Military security is about external attack; almost invariably the parties engaged on legitimate exchange of information are assumed to trust each other. This is not the case in free trade. So, although in this book we shall talk a lot about security, it is important to remember that the real issue is trust.
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RISK ASSESSMENT TO RISK MANAGEMENT
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Access control mechanisms decide whether or not an object request can be granted to a client object.
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Fixer-Uppers. A house that s shabby on the outside may be even worse on the inside. If the lawn and siding have been neglected, the same might be true of the furnace and the roof. Fixer-uppers and handyman s specials are best left for pros, not for f irst-time home buyers. If you do want to try your luck, be sure to have any dilapidated house thoroughly checked out by a house inspector f irst. Bear in mind that your best bet may be a dilapidated house in a good community, even if it costs far more than the same house in a deteriorating community. Gentrif ied neighborhoods areas of cities that are being spruced up tend to be high priced. Your best course may be to look for a house in an area near an already restored section, especially if the houses are impressive brownstones and Victorians. But check with local real estate agents to make sure that the area seems poised to rise again. A basic rule of thumb: Don t spend more buying and f ixing up a house than two thirds of what the house would have cost new. If you buy a house for $60,000 and plan to spend $90,000, the house should be equivalent to a $225,000 new house. Sometimes you can even buy a deteriorated house in an inner-city neighborhood for as little as $1, providing that you promise to f ix it up within a year or two and live there for three years. Check your city housing agency to see if it has an urban homesteading program. Many cities offer low-interest mortgages if you agree to restore a house in a
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To find the quantitative part (that is, the probability distributions), we initialize all node distributions to uniform (equal probabilities for all values). Next we enforce the component laws as well as Kirchhoff s laws (wherever applicable) by zeroing the entries of the probability distributions that correspond to impossible value combinations. Finally we incorporate the manufacturer supplied information about nominal values and tolerances by iterative proportional fitting (see Section 11.1.1), thus setting the marginal component distributions. The resulting graphical model can then be used to diagnose the modeled circuit by propagating node voltage measurements. From the theory of evidence propagation in graphical models and in particular in join trees (cf. Section 4.2.2) it is clear that the computational complexity of operations (iterative proportional fitting and evidence propagation) is governed by the size of the node distributions, which depends on the number of variables in a join tree node and the sizes of their domains (size of the spanned state space). If the distributions can be kept small by a proper selection of cross-sections, the computations are very efficient.
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MEANS, MEDIANS, AND MODES In a statistics class we would usually talk about two other m words, when we talked about means. Those other words are median and mode. The peak is the mode. The median is the point that divides the distribution in half (i.e., half the area of the distribution lies to the right of the median and half lies to the left of it). For a symmetric distribution, the mean, the median, and the mode would all be stacked on top of one another at the peak. As the distribution starts getting a tail to the right, the median moves to the right of the mode, and the mean moves to the right of the median.
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A type selector is the simplest kind of selector and applies a style sheet property to a specific element. The element type is denoted by the element name. In our previous examples, we have been using type selectors to apply different properties to the H1 element. Following is a good example of a set of rules that apply the color green to the elements TITLE, AUTHOR, and PUBLISHER.
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That is, we only need two operations, independent of the number of terms in the disjunction. The reason is that the logical inferences that need to be carried out are similar in structure and thus they can be combined. In Section 3.2 reasoning with relations is studied in more detail.
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