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hand, there are initiatives extracting the information in a content-driven (bottom up) manner. Goal-driven systems, for example, SMES (Declerck and Neumann, 2000), are generally domain speci c and make use of knowledge about the domain in question. The information of interest typically is prede ned as open slots, in so-called templates, which are to be lled by the relevant parts of the text. Goal-driven systems often make use of shallow parsing techniques, and this has led to a renaissance of nite state techniques, for example, augmented transition networks or nite state transducers. Content-driven systems, on the other hand, are designed to work more or less domain-independently. Typically, content-driven systems build up ontologies/taxonomies based on heuristics as well as statistical techniques. Goal-driven and content-driven systems have in common that both of them are highly dependent on a thorough low-level linguistic analysis of a given text, comprising normalization, tokenization and part-of-speech (POS) tagging. As of today, many goal-driven systems perform reasonably well within their domains (for evaluation methods, see, e.g. the MUC conferences). However, their dependency on prede ned domains is a clear drawback and makes them rather unattractive in the Semantic Web context, or for agents or other domain-independent applications. This drawback has led to initiatives that are either trying to make goal-driven systems more domain-adaptive (e.g. SMES; Declerck and Neumann, 2000), or combining them with content driven techniques (e.g. GETESS; Dusterhoft et al., 1999). On the other hand, the domain-independence of content-driven systems comes with a de ciency in terms of performance. The lack of accuracy makes content-driven systems somewhat inappropriate as tools for extracting information units that require a high degree of precision (e.g. knowledge base generation). However, their fuzziness is an important feature when it comes to tasks dealing with uncategorized texts such as summarization or agent-based searching.

CREATE TABLE XMLGeneric ( ID INT IDENTITY NOT NULL PRIMARY KEY, Data XML (SchemaName) )

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Gate Voltage Vg (V) Figure 6.25 Hot-carrier degradation as a function of gate voltage. The different curve represent the different gate oxide splits. The nitrided oxides (NO) and reoxidized nitrided oxide (ONO) greatly reduce the peak of the hot-carrier damage. (After Hori et al., Ref. 120, 1992 IEEE.) metal pad. The pad, covered with resist, is in contact with the unprotected deposited metal until the exposed metal has been completely etched. No charge builds up on the pad until this point. Once the unprotected metal is completely removed, the charge begins to build up on the exposed metal sides at the edge of the resist mask. 94 The longer the overetch, the greater the buildup of charge. 92 The damage itself takes the form of interface states, slow interface states, 9 8 and positive hole traps. 92 This damage appears not be annealed out-interface states reappear after an alloy anneal, 99 and the hole traps remain, even after anneals as high as 9000C.100 Plasma damage has a significant effect on the hot-carrier hardness of the oxide.99 ,101 This added susceptibility comes from the prestressing of the gate oxide by Fowler-Nordheim injection that arises during the plasma processing. Initial measurements appeared to show that n-MOS transistors were affected by antenna ratios. However, later work99 showed that the n-MOS was much less susceptible to interface state generation but that it had increased electron trapping (at Vg = Vd). More striking was the decrease in p-MOS hot-carrier susceptibility. 98 The p-channel device shows a very marked increase in damage under electron trapping conditions (Vg just above threshold). In summary, the damage in both n- and p-MOS under hot-carrier stress for unprotected device with large antenna ratios takes the form of increased electron trapping susceptibility.

1. Draw the sketch, either the plan view or skyline. The sketch represents the top of the Rib. Material can only be added between the sketch and the rest of the part.

14. Create an extruded cut that goes Through All using the End Conditions options. If you get an error, then try reversing the direction of the extrude. Figure 7.62 shows the state of the model up to this step.

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From its early beginnings as DARPANET, linking a select few military and Research and Development (R&D) facilities, the Internet has grown to comprise thousands of networks and millions of users in virtually every country in the world. The Internet is the kudzu of networks, growing like the uncontrollable weed of Southern infamy. The Internet truly was the information superhighway, long before the term was coined. While actually more of a private road, it was characterized by a sense of truly unparalleled freedom. That early network stood apart by virtue of its providing free and open access to information that characteristic remains today as the hallmark of the Internet. The Internet is a network of networks and has become a Global Village, much as envisioned by Marshall McLuhan (1911 1980), education, philosopher, and scholar. In some sense, at least, the Internet is the information superhighway.

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