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organization. This automatically ensures that architectural investments become an integral part of the business investments necessary to achieve concrete business objectives. Architecture must be developed just enough, just in time. Concrete guidelines for implementing the just-enough, just-in-time principle are discussed in full in 6, Architectural Services. We shall see that one of the ways in which this principle manifests itself is the way in which the architectural team is manned: There is a small, fixed team of architects that, depending on the workload, can be temporarily increased by employees from the line organization. Just enough, just in time will also be ensured by involving architects from the outset that is, during the definition of business cases. The ability to recognize the different levels of abstraction within architecture is helpful in developing just-enough, just-in-time architecture. Working under architecture is supported by a theoretical and working model. A model has been developed for working under architecture that contains all of the important elements of architecture: the dynamic architecture itself, the three main processes of architecture, and the governance of architecture. Transparent relationships must be defined. An architectural framework is an important tool for an architect and is discussed in detail in 6. The architectural framework provides clear insight into the relationships in an organization. Several development strategies are distinguished. This principle is translated directly into the three development strategies: (1) the anticipatory strategy for working under architecture and (2) the defensive and (3) offensive strategies, in which certain aspects of architecture are temporarily ignored. Architectural principles and processes must be an integral part of the organization. The focus of the model lies on architecture as a process, encompassing the whole trajectory from determining business objectives to creating IT solutions. Moreover, the model stresses the importance of a strong commitment from top management.

ACTIVITIES If you are required to complete a research project as part of your program of graduate studies and the project will involve human subjects, obtain a copy of the application you must complete for review and approval of research by your university Institutional Review Board (IRB). Gather sample consent and assent forms from faculty who have conducted research projects with children.

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of rm ensembles, and need to be calibrated to individual exposures through a time dependent multiplier, a(t):

How comfortable are you with employees taking greater responsibility for evaluating and selecting health plans, coverage, and providers

It s always a good idea to check your assumptions about device capabilities instead of just going ahead and calling functions that may fail (or worse) because the support is not there.

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Like the corresponding alternative to the 2 measure in the probabilistic setting, this measure appears to be more natural. Weighted Sum of Degrees of Possibility As a global possibilistic evaluation measure we discussed in Section 7.1.3 the weighted sum of degrees of possibility. For a given graph G and a given database D = (R, wR ) it is defined as [Borgelt and Kruse 1997b] Q(G) =

A software system using CBR and fuzzy logic, named CREW [25], was developed to simulate a time-series model of astronaut crews. Without the expense and risk of actual ights, it can predict how a given crew might respond to mission stress under different scenarios. In the frame of CBR, some adaptation rules, coming from the statements of researchers, act as a supplement to the case base. The conditions of these rules are often described by linguistic terms such as low, medium, and high with modi ers such as very or not. The nonquantitative nature of these rules lends itself to formulation and computation using fuzzy logic. They are translated reasonably into numeric computations by the de ned membership functions, preserving suf cient precision considering the limited effect that any given rule or condition has on the overall simulation. In 2002, Passone et al. [26] provided an application of CBR technology to support the design of estuarine models (i.e., models for evaluating water quality). The system aims to help nonexpert users to select a model that matches their goal and the nature of the problem to be solved. It consists of three components: a case-based reasoning scheme, a genetic algorithm, and a library of numerical estuarine models. Once an appropriate model procedure is selected using the case-based reasoning scheme, a genetic algorithm with problem-speci c knowledge is activated to adjust the model parameters. An example based on the Upper Milford Haven estuary in the United Kingdom is used to demonstrate the ef ciency of the system s structure for supporting estuarine model design.

For half-wave spacing this approach and that of Dolph give identical results! In fact, owing to the properties of the Chebyshev polynomial, the two space factors, in precursor form, are equal:

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