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Scalar quantisation and rescaling ( 3) can be implemented by division and/or multiplication by constant parameters (controlled by a quantisation parameter or quantiser step size). In general, multiplication is an expensive computation and some gains may be achieved by integrating the quantisation and rescaling multiplications with the forward and inverse transforms respectively. In H.264, the speci cation of the quantiser is combined with that of the transform in order to facilitate this combination (see 6).

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R. The second graph in Figure 10.8 depicts the discrete probabilities of the same portfolio with risk-mitigating market instruments included. There are a couple of points to remark upon before continuing. Remarks The purpose of hedging is to reduce uncertainty. Uncertainty of the hedged portfolio is less than that of the unhedged portfolio because outcomes are more clustered about the mean. The unhedged portfolio has a wider distribution. Hedging generally reduces the expected value of the portfolio. In the graph in Figure 10.7 the expected value of the unhedged portfolio is $7.55 million, while the expected value of the hedged portfolio, Figure 10.8, is $6.34 million. The difference in expected values is a price that is paid for reducing the uncertainty.

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Education researchers Tashakkori and Teddlie (1998) place their mixed model work within the philosophical framework of pragmatism, based on the work of several authors (see Cherryholmes, 1992; Greene, 1994; House, 1994; Howe, 1988; Murphy, 1990 and Rorty, 1982 as cited in Tashakkori and Teddlie) The research question is the primary determinant of the methods used Tashakkori and Teddlie see pragmatism as the best philosophical t for mixed methods because it avoids the either or approach of positivism and constructivism and advocates the use of the best methods to best answer the research question Additional frameworks have been developed by various scholars to support the use of mixed methods with a concomitant emphasis on context Examples include falliballistic realism (Manicas and Secord, 1983), scienti c realism (Kazi, 2000), and a developmental approach (Bronfenbrenner, 1979) Therapeutic jurisprudence ts well within each of these.

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A fourth inherent quality of therapeutic jurisprudence is that it provides an invitation to look at the legal process from a multitude of perspectives often previously overlooked It broadens the who of who is studied, to include each person directly or indirectly involved in the legal process itself In many cases, this means considering those who previously had no voice, such as involuntary patients (Perlin, 2000) and victims of domestic violence (Winick, 2000a) Or it can include a practitioner, a criminal defendant, a victim, or society as a whole Empirical research, thus far in therapeutic jurisprudence, has focused mostly on how mental health professionals and plaintiffs perceive an aspect of the legal process (Anderson et al, 1996; Ferencz and McGuire, 2000; Greer, O Regan and Traverso, 1996; Kennedy, 2001; Poythress and Brodsky, 1996; Susman, 1996; Zito et al, 1993).

Figure 3.4 provides graphs of the power consumption and corresponds to the equations. Note the difference between this equation and the equation for the power consumed by the resistor. The power input into the resistor is never negative; the resistor is always consuming power. The power input into reactive elements oscillates from positive to negative, back to positive, and so forth. Whenever the power input is positive, power ows from the generator to the reactive element. Whenever the power input is negative, the reactive element returns power to the system generator. In the graphs the amplitude of the power requirement for the inductor is larger than that of the capacitor. This is solely for the purpose of differentiating the curves. The energy consumption of inductors and capacitors is the following: Energy(t ) = Vmax cos(2 t ) 4L 2 Energy(t ) = CVmax cos(2 t ) 4

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