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Tradeoffs: decreased network performance, loss of server s complete control over system behavior Note that the deployed Web extensively uses cookies (caching server state on the client), which breaks this constraint 3 Caching some representations may be cached Intermediaries may respond on behalf of a server with the cached data Gains: ef ciency, scalability, and user-perceived performance Tradeoff: potential reliability 4 Uniform interface consistent interfaces for resource identi cation, resource manipulation through representations, self-describing messages, and messages as the embodiment of application state Gains: simplicity, visibility, independent evolvability Tradeoff: ef ciency 5 Layered system each component knows only about the components with which it is interacting Gains: bounds system complexity, independent component evolvability, legacy encapsulation, simpli es components by moving infrequently used functionality to a shared intermediary, and intermediaries can be used to improve system scalability by enabling load balancing.

Enables security policies to be enforced on data crossing the organizational boundary ( rewalls) Tradeoffs: adds overhead and latency to the processing.

6 5 4 3 2

14. 15.

Reification of DSM-IV entities, to the point they are considered to be equivalent to diseases, is more likely to obscure than to elucidate research findings. . . . All these limitations in the current diagnostic paradigm suggest that research exclusively focused on refining the DSM defined syndromes may never be successful in uncovering their underlying etiologies. For that to happen, an as yet unknown paradigm shift may need to occur. (p. xix)

Do they charge separately for authorizations and settlements Can settlements be done in real time or batch Do they support address veri cation system (AVS), card

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Let A and B be two integer numbers such that A B, or equivalently let A and B be two polynomials such that deg(A) deg(B). The initial conditions are r 1 = A and r0 = B. In a recursive calculation, and in the ith recursion, the value ri is obtained as the remainder of the division of ri 2 by ri 1 ; that is, ri 2 = qi ri 1 + ri where ri < ri 1 or, for polynomials, deg(ri ) < deg(ri 1 ). The recursive equation is then ri = ri 2 qi ri 1 Expressions for si and ti can also be obtained as ri = si A + ti B The recursion (38) is also valid for these coef cients: si = si 2 qi si 1 ti = ti 2 qi ti 1 Then r 1 = A = (1)A + (0)B r0 = B = (0)A + (1)B (41) (40) (39) (38) (37)

32. A. Beex, J. Zeidler, Non-Wiener Effects in Recursive Least Squares Adaptation, Proc. 7th Int. Symposium on Signal Processing and Its Applications, Vol. 2, 2003, pp. 595 598. 33. D. Erdogmus et al., Recursive Principal Components Analysis Using Eigenvector Matrix Perturbation, EURASIP J. Applied Signal Processing, Vol. 13, pp. 2034 2041, 2004. 34. M. Woodbury, Inverting Modi ed Matrices: Memorandum Rept. 42, Statistical Research Group, Princeton University, Princeton, NJ, p. 4, 1950. 35. M. Brookes, The Matrix Reference Manual. London: Imperial College, 2005. 36. UC Irvine Machine Learning Repository, http://archive.ics.uci.edu/ml/databases/eeg/eeg. data.html.

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It must be an identifier. It cannot be a keyword or an ActionScript literal such as true, false, null, or undefined. It must be unique within its scope. (See Scoping a variable on page 220.)

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(a) Find the self-information associated with each symbol, and the entropy of the source. (b) Calculate the maximum possible source entropy, and hence determine the source efficiency. 1.2 (a) Calculate the entropy of a DMS that generates five symbols {A, B, C, D, E } with probabilities PA = 1/2, PB = 1/4, PC = 1/8, PD = 1/16 and PE = 1/16. (b) Determine the information contained in the emitted sequence DADED.

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