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So far, you ve looked at de ning functions using a function statement. There is an alternative way to de ne functions; ActionScript also supports anonymous functions or function expressions. Anonymous functions are so called because they have no name. They can be passed around, stored in variables, and run by other code. Anonymous functions are particularly useful when using a programming style called functional programming; you won t see much of them until 8, Arrays, and only infrequently thereafter. To create and store an anonymous function, write a function statement, leaving out the name, and then assign it to a variable of your choosing with a type of Function, as shown:

When the parameters and are unknown, we usually estimate them on the basis of preliminary samples, taken when the process is thought to be in control. We recommend the use of at least 20 to 25 preliminary samples. Suppose m preliminary samples are available, each of size n. Typically, n will be 4, 5, or 6; these relatively small sample sizes are widely used and often arise from the construction of rational subgroups. Let the sample mean for the ith sample be Xi. Then we estimate the mean of the population, , by the grand mean

var doSomething:Function = function (arg:Object):void { // function code goes here. }

(16-3)

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Thus, we may take X as the center line on the X control chart. We may estimate from either the standard deviation or the range of the observations within each sample. The sample size is relatively small, so there is little loss in ef ciency in estimating from the sample ranges. The relationship between the range R of a sample from a normal population with known parameters and the standard deviation of that population is needed. Since R is a random variable, the quantity W R , called the relative range, is also a random variable. The parameters of the distribution of W have been determined for any sample size n. The mean of the distribution of W is called d2, and a table of d2 for various n is given in Appendix Table X.

Anonymous functions behave slightly differently from function declarations. Most importantly, they are an expression rather than a declaration. They de ne and evaluate to an object of type Function.

W d3 (16-4)

TABLE 3-1

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Can be called at any point in the code regardless of where in the code the function is de ned. Can be called as a method by using dot syntax; acts as part of the object s interface. Belongs to the object it s de ned on. Cannot be rewritten or deleted.

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Like a variable declaration, is available only in the scope the function is de ned. Cannot be used as a method. Exists in scope it s de ned in. Anonymous functions stored in variables can be reassigned a new value or deleted.

Therefore, we may use as our upper and lower control limits for the X chart UCL De ne the constant A2 X LCL 3 d2 1n X (16-7)

(16-8)

For most situations, I recommend that you use function declarations rather than anonymous functions in your code. Their consistency and ease of use make them the superior choice. However, sometimes using a function expression can provide exibility and usefulness that a function statement cannot. These may include the following: Functions that need to be used only once Functions useful only within another function Changing the functionality of a method at runtime Passing a function Using functional programming paradigms like Array.map()

Now, once we have computed the sample values x and r, the X control chart may be de ned as follows: X Control Chart (from R )

This approach represents hierarchical data collection and processing, where a three-level tree is formed in the network At the topmost level, the supervisor task collects information about gradient violation notifications At the middle level, exactly 8 Monitor tasks collect the data from their non-overlapping domains and determine if the gradient between neighboring nodes in their domain exceeds the prespecified threshold At the lowest level of the tree, temperature sampler tasks at each node periodically produce the Temperature data items that contain sensor readings Another possible ATaG program that we implement in this use case is shown in Figure 53 The approach in this program is to accomplish the desired overall functionality by means of interactions between neighboring sensor nodes The abstract tasks in this program are the same as the tasks in the hierarchical data processing approach.

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