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seismic velocities, and layer 3 is absent. The crustal thinning may extend several tens of kilometers from the fracture zone. Geologically, this structure may represent a thin, intensely fractured and hydrothermally altered basaltic layer underlain by serpentinized ultrama c rocks. The apparent thickness variations may re ect different extents of serpentinization. The thin ma c crust is thought to be a result of reduced magma supply at ridge offsets as noted in Section 6.7. Ocean fracture zones must bring oceanic crust of different ages into juxtaposition. The depth of the sea oor is dependent upon its age (Section 6.4), and so it would be expected that a scarp would develop across

to understanding a complex expert system. That said, each diagram has its own bene ts and uses. A hierarchic model such as TransMode Hierarchy is more appropriate when a user doesn t want to become bombarded with implementation details but would rather see the bigger picture; on the other hand, a rule trace diagram is preferable when more case-speci c detail is sought after what speci c variables and actions an inference engine undertook to reach a decision, the pathway taken through the knowledge base. Together, both diagrams can be useful in revealing expert system actions. Because rule trace diagrams are intended to represent the logic of speci c rules, such diagrams may employ notation to represent more complex Boolean expressions in the condition part of the rule. First of all, special notation is needed to represent both conjunctive (AND) conditions as well as disjunctive (OR) conditions. See Figures 6.9 and 6.10 for the notation that can be used to differentiate the two types of conditional expressions. The difference in the notations is that in conjunctive conditions only one arrow points to the conclusion, whereas in disjunctive conditions separate arrows point from each of the conditions to the conclusion node. This notation is similar to that of the argument diagrams described in 4, a type of diagram used to illustrate the structure of an argument (see the discussion on the difference between conjunctive and convergent arguments on p. 113). More complex Boolean expressions containing both ANDs and ORs can also be diagrammed using a combination of the notations. For example, see Figures 6.11 and 6.12. Figure 6.11 illustrates the conditional expression (A and

They randomised 212 patients with osteoarthritis of the knee to receive either the glucosamine.

The situation is problematic because the binding mechanism obviously has to work in both directions Unfortunately, changing the outbound binding behavior requires modifying either the BeanUtils package or the Struts framework itself Therefore, most developers find it expedient to skirt the issue by coding String (or Boolean) properties in their ActionForms to represent each of the HTML form values expected in the request This defers inbound type conversion until after validate() has been called, at the cost of making conversion an additional, separate step for which the developer is now responsible The pitfalls described in this chapter assume that ActionForms follow this pattern Because the Struts framework doesn t provide built-in support for formatting, it doesn t provide a complete solution for type conversion and only recently added support for validation Developers often resort to hand-coding the functionality wherever it is needed.

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This usually results in the scattering of formatting, type conversion, and validation code across a number of classes, and all too often leads to copying and pasting of functionality between methods, as described in the pitfalls in this chapter..

The likelihood function can also be written as (1 - p)". 1-P Consider now the detection problem of deciding if the sequence S 1 or the sequence S2 was sent, where each occur with equal probability. The maximum likelihood decision rule says to choose that value of S for which &dH(R3S) (1 - p)" is the largest. Assuming that p < this corresponds to choosing that value of S for which dH (R, is the smallest, that S) is, the vector S nearest to R in Hamming distance. We see that for detection in a Gaussian channel, the Euclidean distance is the appropriate distance for detection. For the BSC, the Hamming distance is the appropriate distance for detection.

String password = req.getParameter(PASSW0RD); / / Set up the JDBC connection try { / / Create a JDBC driver Class.forName(DRIVER-NAME).newInstance(); connection = DriverManager.getConnection(CONNECTI0N-URL);

See Figure 8.4 for the belief network and how the certainty factors are propagated in the network. Based on these user responses, the system calculates the certainty factors for each of the rules that is, cf(rule) = cf(premise) cf(conclusion):

M([OOI, r) = 10g2(l - p c ) Thus the longer path is has a better (higher) Fano metric than the shorter path.