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Figure 5-24 A weak entity is one that cannot be identi ed by its attributes alone. For example, consider a database to store submarine race results. A Race entity holds information about particular race. A Result entity holds information about how a submarine performed in a race. The Result entity has attributes to store a reference to the Race entity, a reference to a Sub entity, and result information such as Time, FinishPosition, and TorpedoesFired. Alone, there s no reasonable way to nd a speci c Result entity. There is no combination of Result attributes that really makes sense as a search key. You could search for a combination of Time and FinishPosition but that doesn t identify a particular Result. Instead you would either search for a particular Race and use it to nd its associated Results, or search for a particular Sub and use it to nd its associated Results. In an ER diagram, you draw a weak entity with a thick rectangle and connect it to its identifying relationship with a thick arrow. Figure 5-25 shows the Race, Sub, and Result entity sets and their relationships.

Specify starting width <0.0000>: .5 Specify ending width <0.5000>: .25

A shortcut for Application.ActiveDocument is ThisDrawing, and so you can also use:

Each variable is sampled over its own periodicity, in analogy with what has been described above: in this way, a two-dimensional grid of samples is obtained. If the signal has a limited frequency spectrum, and if the number of samples satis es Nykvist s theorem, we can compute the two-dimensional grid of coef cients in the two-dimensional Fourier series expansion (eq. (1.101)); the details are given in the Appendix A.7. The samples are taken at the sampling time instants, tk1 = T1 k1 , 2N1 + 1 k1 = N1 , . . . , N1 , tk2 = T2 k2 , 2N2 + 1 k2 = N2 , . . . , N2 (1.105)

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There are a number of serious difficulties with traditional parameter estimation methods. The most important of these are the following:

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The ARRAY command creates a rectangular or polar (circular) pattern by copying the object(s) you select as many times as you specify. The ARRAY command is a powerful drawing tool. It can quickly create large numbers of objects, thus saving a huge amount of time and effort.

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A management information base (MIB) is a database that contains manageable objects and variables of these objects pertaining to a network node, for the purpose of node management within a network. SNMP itself is not able to de ne details for the information it retrieves; that is what a MIB is there for. The reason to keep MIBs and SNMP as separate standards is simple. This allows the management station to monitor multiple nodes, many with a different set of MIBs speci c to the node. A MIB is con gurable and can be updated. If a node is upgraded to support new and/or approved standards, the MIBs can be updated on the manager to match what is available on the agent.

Figure 18-38: An office building plan layout. 5. Choose Modify Object Attribute Global. Follow the prompts:

Summary

A dotted pair is a special type of list that contains only two elements. Some AutoLISP functions do not accept dotted pairs as an argument, but they re used to represent AutoCAD database objects. To construct a dotted pair, use the CONS function:

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public class CommandLineExample {

is long, although they account in total for less than 5% of cases among adults in westernized and developing countries In the remaining 95% of cases with no identi able underlying cause (at least using current diagnostic methods), obesity has been variously described as common , idiopathic or lifestyle-related Overall, common obesity can be attributed to the impact of obesogenic lifestyle factors on individuals who have a variable genetic susceptibility to fat gain Across populations, lifestyle changes such as decreased levels of everyday physical activity and increased consumption of energy-dense foods can be related to the spread of obesity, and in general terms, common obesity can be attributed to a cumulative excess of energy intake over expenditure However, there is no doubt that common obesity is a heterogeneous condition, and that the term idiopathic simply re ects the inability of available investigative methods to make a more precise diagnosis.

Existing evidence already points to differing genetic susceptibilities for obesogenic factors as diverse as social facilitation, preference for energy-dense foods and the capacity to store triglyceride rather than oxidize fatty acids (see s 7 and 8) Other obesity susceptibility genes will undoubtedly be identi ed, and ultimately it may prove possible to subdivide common obesity into categories de ned by an individual s genetic susceptibility pro le However, the vast majority of common obesity appears to be a polygenic trait, and the contribution of any individual susceptibility gene is likely to be small In the same way that genetic predisposition varies widely between individuals, there are considerable individual and population differences in environmental exposure to factors such as the availability of energy-dense food and opportunities for active exercise or sedentary pursuits.

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