.net core qr code reader

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the description of each scenario as explicit as possible. A sequence diagram (see Fig. 6.7) has a time line associated with each major actor (our system and other systems) in the scenario. The systems involved are listed across the top of the diagram with the time lines running vertically down the page under each of the systems. Time moves from top to bottom in an input/output trace; the system of concern is highlighted with a bold label and heavier line. Interactions involving the movement of data, horizontal arcs from the originating system to the receiving system, designate energy or matter among systems. A label is shown just above each arc to describe the data or item being conveyed. Doubleheaded arcs are permissible to represent dialog in a compact manner. Having two or more arcs in quick succession is also common to illustrate that the same item is being transmitted from one system to multiple systems or multiple systems are potentially transmitting the same item to one system. Figure 6.7 shows the rst of these scenarios documented as an input/output trace diagram. See the elevator case study on the author s web site for more examples. The purpose of these sequence diagrams is to be more explicit than written text can be about the systems involved with a speci c focus on the time-based interaction of systems and the transmission of data and items. Compare the sequence diagram in Figure 6.7 to the rst scenario in Table 6.4. These sequence diagrams are not meant to be exact representations of dynamic interaction. An interval time scale is not being represented; rather time is ordinal any arc that

The statistical properties of the estimates obtained using high-resolution methods have been studied extensively, primarily in the context of estimating the frequencies of superimposed complex sinusoids from noisy measurements [15, 16, 24]. Expressions for the mean square error (MSE) of the frequency estimates suggest that the numerical performance of such methods is very close to the Cramer Rao bound [26], which represents the lowest achievable MSE by any unbiased estimator, such as an ML estimator. A detailed presentation of the statistical properties is fairly involved and we will not pursue any such analysis here. However, we give simpli ed expressions for the MSE of the frequency estimate in the case of a single exponential (with amplitude a1 ), which, in our framework, corresponds to the estimate of the time delay t1 of the dominant path. Consider rst the subspace-based approach from Section 2.2.4. Let the data matrix Ys be of size P Q, and let N P Q 1 be the total number of DFT coef cients Ys n used for estimation. Recall that the coef cients Ys n are obtained from the bandpass version of the received signal y(t), that is, Ys n Y n =S n , n [ N1 , N1 N 1 , Equation (2.8). If we de ne v1 v0 t1 , and assume that the signal and noise are uncorrelated, the MSE of the state space approach can be expressed as [15] 8 2 1 sn N > > > > Q(N Q)2 ja j2 P jS n j2 , for Q N=2 > 1 < n (2:32) E{Dv2 } % 1 > > 2 > 1 sn N > > , for Q . N=2 : 2 P Q (N Q) ja1 j2 n jS n j2

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LEVEL OF EVALUATION (COLA + DEPT HEAD EVAL)

END POINT Projects differ from the ongoing operations of a firm in that they are temporary and unique. These qualities mean that factors like personnel management, lines of authority, budgeting, accounting controls, and communication need to be handled differently in the project environment. The project management techniques discussed in this book have evolved to meet these challenges. Modern project management evolved from the giant defense projects during and after World War II. These endeavors were so enormous that normal management techniques proved inadequate. In addition to technical knowledge, managers of projects came to need business skills and the new skills related to managing temporary and unique projects. Project management techniques have now become industry-independent, even though each project manager must have skills specific to his or her industry. Successful projects deliver a high-quality product on time and on budget. Project managers, however, need to be aware that everyone involved in a project all the stakeholders must agree on what success means. Managing expectations is one of the main jobs of a project manager. Success depends on the manager guiding the project through four stages in its life cycle: definition, planning, execution, and closeout. One of the reasons for the present popularity of projects is the growing number of new products. Product development employs a process roughly similar to that of projects; the differences are that a product development life cycle describes the work required to create the product, while a project life cycle focuses on managing the work. This need for new projects has brought about the creation of companies organized around doing projects project-oriented organizations.

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