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A related model is based on a representation of the constraints by the minimum distance that must exist between pairs of cells that are assigned channels a fixed distance apart in the radio spectrum (see [26, 37], for example). More precisely, a set of nonincreasing parameters d0, d1, . . . , dk is given and a channel assignment f has to fulfill the condition that for any pair of nodes (cells) u and v i f (u) and j f (v) and |i j| = d(u, v) > d
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4. Insert the following procedure into the code module for the ThisWorkbook object:
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Figure 4.1 A hexagon graph with a 3-coloring.
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FIGURE 15.24. Correlated source encoding.
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Now that you ve got the array populated, it s time to generate the random number that plucks a quote from the array. When you use the random method of the Math object, it generates a random value between 0 and 1. You could just multiply the random method of the math object by 70 to generate a quote, but that wouldn t leave you any room for future expansion. If you add or delete elements from an array, you have to remember how many elements are currently in the array and change the script accordingly. Instead of relying on a set numeric value to generate the random number, you use the length property of the Array object. When you add this to your script, Flash checks the array length and knows the exact number of elements in the array. In the future, when you add or subtract elements from the array, Flash evaluates the array length and knows the number of elements currently in the array. To generate the random number: 1. Click Actions Variables and double-click setVariables. 2. In the Variable field, type rndNum and then place your cursor in the Value field. 3. Click Objects Core Math Methods and double-click round. The text Math.round() appears in the Value field. 4. Place your cursor between the parentheses, and in the left pane of the Actions panel, Click Objects Core Math Methods and then double-click random. The method is added to your script, and the text Math.random() appears in the Value field. 5. Place your cursor between the parentheses and type rndQuote. 6. In the left pane of the Actions panel, click Objects Core Array Properties and then double-click length. Click the Expression checkbox. Your finished ActionScript for the first frame should look like Figure 8-6.
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Concentration time and physical preparation time increased with kick difficulty; the kicker reported on the use of a number of psychological skills in his preparatory routine.
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2. IN VITRO CULTIVATION OF ENGINEERED TISSUES 2.1. Overall Approach There is a serious lack of suitable donor tissues for transplantation, along with an increasing number of patients in need of transplantable tissues and organs. The disparity between the need and availability of donor tissues has motivated the tissue engineering approach, aimed at creating cell-based substitutes of native tissues. The overall concept of tissue engineering is depicted in Fig. 6.1. Living cells are
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Many people find it helpful to use a name that also identifies the type of object. In the preceding example, I use ob as the prefix to identify the fact that this control is an OptionButton.
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INTRODUCTION
In general, for an erroneous path of weight d, 1 2
as possible (e.g., by offering child care during interviews for working participants, by providing transportation, or by using phone interviews). Incentives for participation may be offered. Funds to support the tracking of participants should be included in evaluation budgets, and lower-cost options should be attempted before moving on to more costly tracking efforts. To prevent condition-related attrition, it is especially important to consider the features of the different conditions that may in uence the relative desirability of participation. Sometimes, special incentives can be offered in the otherwise less-attractive condition, as long as this does not obscure the program effect of interest or create any ethical problems (for additional suggestions on reducing attrition and tracking clients over time, see Ribisl et al., 1996). Despite the best use of preventive steps, some attrition may occur. One after-the-fact approach to attrition is to analyze data as though all participants received the treatment to which they were initially assigned. This approach is often called intent-to-treat (ITT) analysis. The ITT approach will typically provide a conservative estimate of the treatment effect because some portion of those assigned to the treatment did not in fact receive it. Obviously, the ITT analysis also requires that outcome measures be available even if the person dropped out of the assigned condition (or switched to another condition). In general, if the ITT approach is used, the results of this analysis should be reported in conjunction with other analyses. Another approach is to replace missing data. Considerable work has been done in the last two decades on data imputation (e.g., Rubin, 1987; Schafer, 1997). As Graham and Donaldson (1993) demonstrated, taking extra steps to obtain outcome data from a sample of dropouts can greatly aid in the imputation of missing data. In addition, other kinds of analyses, summarized next, can be used in an attempt to adjust for any nonequivalence that is created by attrition. Again, multiple analyses, using alternative ways of dealing with missing data, are suggested as a way to increase con dence that the conclusions of an evaluation do not ride on some single (and perhaps incorrect) set of assumptions that underlie a single form of analysis (Shadish et al., 2002). Statistical Adjustments A variety of statistical techniques, including the analysis of covariance (ANCOVA), latent variable structural equation modeling, selection modeling, and propensity scores, can be used to try to adjust for nonequivalencies introduced by attrition in randomized experiments. However, these techniques are more commonly discussed in terms of their use in quasiexperiments, where the absence of random assignment often
which leads into a series of equations: J /C 1 n1 S 1 = N1 /n1 S 1 N2 /n2 S 2 J /C 2 n2 S 2 = N2 /n2 S 2 N3 /n3 S 3 . . . G J /C G n G S = NG /n G S G NG +1 /n G +1 S G +1
Psychological interventions aimed at change in individuals and systems.
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