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buoyant support The support offered by groundwater to the roof of a cave (or other ooded underground void). capillary fringe A thin mantle immediately overlying the water table (q.v.) in which the pores are entirely lled with water, but the water pressure is less than atmospheric pressure. capillary fringe conversion Process by which the water table rises very rapidly by a height equal to the prior thickness of the capillary fringe, as tension-saturation changes to pressure-saturation. capture zone A synonym for borehole catchment (q.v.). casing A well lining with solid walls, typically xed in place with an impermeable grout. (Casing is usually installed above the water table, but can also be used below the water table to seal off undesired horizons from the well.) catchment The entire surface area feeding runoff to a given point on a surface water drainage system.

Among these parameters, paging delay is the main focus of location proximity algorithms because paging delay can in uence the availability of location information The higher frequency at which the mobile station updates its location, the smaller the paging area of cellular network So, the optimization problem is to nd the optimal location update and paging algorithms and to minimize the totalcost Many schemes are surveyed by Zhang [19] One scheme is to de ne a location area that covers a few basestations and a mobile station updates its location whenever it comes into a new location area In this scheme, before paging succeeds, the location proximity is the current location area Another scheme is called the movement-based location update scheme, in which each mobile station keeps a counter that is initialized to zero The count increases by one whenever the mobile station crosses a cell border.

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(i) If one is interested in using regression analysis in a strictly descriptive manner, with no inference and no model building, one need not worry quite so much about assumption validation (j) In a normality plot, if the distribution is normal, the bulk of the points should fall on a straight line (k) The chi-square distribution is left-skewed (l) Small p-values for the Anderson Darling test statistic indicate that the data are right-skewed (m) A funnel pattern in the plot of residuals versus ts indicates a violation of the independence assumption 22 Describe the difference between the estimated regression line and the true regression line 23 Calculate the estimated regression equation for the orienteering example using the data in Table 23 Use either the formulas or software of your choice 24 Where would a data point be situated which has the smallest possible leverage 25.

When the count reaches a prede ned number M, the mobile station updates its location In this case, before paging succeeds, the location proximity is a circle centering at last updated cell and having a radius of M cells Considering the zigzag behavior between two adjacent cells, the actual position may be quite close to the previous updated cell A variation of this scheme is called distance-based location update strategy In this area, a mobile station updates its location only after it is more than distance M from previous updated cell In this.

Calculate the values for leverage, standardized residual, and Cook s distance for the hard-core hiker example in the text 26 Calculate the values for leverage, standardized residual, and Cook s distance for the eleventh hiker who had hiked for 10 hours and traveled 23 kilometers Show that although it is neither an outlier nor of high leverage, it is nevertheless in uential 27 Match each of the following regression terms with its de nition..

7Delay spread is a variance in delay due to dispersion of emitted signals on delayed paths due to re ection, diffraction/ refraction. Lee reports a typical urban delay spread of about 3 ms.

Example 14.2.8 (Sequence of n bits with k ones) Can we compress a sequence of n bits with k ones Our rst guess is no, since we have a series of bits that must be reproduced exactly. But consider the following program:

Figure 20.1 shows the difference between the linear and logistic functions for P(Y = 1). The logistic function (as well as the probit function) is called a sigmoid, meaning S-shaped, curve. It should be clear that the right-hand side of Equation 20.4 can never fall outside the 0,1 range. The function approaches 0 as 0 + 1 X becomes increasingly negative, and approaches 1 as 0 + 1 X becomes increasingly positive, as shown in the gure. (For illustration purposes, it is assumed that 1 is positive.) In the linear speci cation for

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