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In this plot, the height of each bar is the total number of observations that are less than or equal to the upper limit of the bin Cumulative distributions are also useful in data interpretation; for example, we can read directly from Fig 6-10 that there are approximately 70 observations less than or equal to 200 psi When the sample size is large, the histogram can provide a reasonably reliable indicator of the general shape of the distribution or population of measurements from which the sample ~ was drawn Figure 6-11 presents three cases The median is denoted as x Generally, if the data are symmetric, as in Fig 6-11(b), the mean and median coincide If, in addition, the data have only one mode (we say the data are unimodal), the mean, median, and mode all coincide.

package { import flash.display.*; import flash.events.Event; import flash.events.KeyboardEvent; import flash.events.TimerEvent; [SWF(frameRate="2")] public class ch36ex16 extends Sprite { protected var bmp:BitmapData; protected var stitch:Boolean = false; public function ch36ex16() { bmp = new BitmapData(200, 200); var shape:Shape = new Shape(); shape.graphics.lineStyle(0, 0, 0); shape.graphics.beginBitmapFill(bmp); shape.graphics.drawRect(0, 0, stage.stageWidth, stage.stageHeight); shape.graphics.endFill(); addChild(shape); stage.addEventListener(KeyboardEvent.KEY_DOWN, onKeyDown); addEventListener(Event.ENTER_FRAME, onEnterFrame); } protected function onKeyDown(event:KeyboardEvent):void { stitch = !stitch; } private function onEnterFrame(event:Event):void { bmp.perlinNoise(100, 100, 2, Math.random()*1000, stitch, false, 1, true); } } }

If the data are skewed (asymmetric, with a long tail to one side), as in Fig 6-11(a) and (c), the mean, median, and mode do not coincide Usually, we nd that mode median mean if the.

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Using the offsets parameter to offset individual octaves of Perlin noise can generate interesting effects. For a good example, look ahead to Example 37-13 (http://actionscriptbible.com/ ch37/ex13). In that example, you use Perlin noise to simulate wind rippling a ag. The bigger octaves move more slowly because the prevailing power of the wind uctuates slowly, whereas smaller octaves move faster, pushing small ripples by much faster in addition to the overall motion.

(S14-15)

Summary

and the rst-order response surface, that is, the contours of y, is a series of parallel lines such as that shown in Fig. S14-7. The direction of steepest ascent is the direction in which

A bitmap is a grid of colors, one for each pixel. Bitmaps in Flash Player store 32 bits per pixel in four 8-bit channels: alpha, red, green, and blue. With bitmaps, you have total control over what goes on the screen. Use this to write anything from a simple effect to your own graphics engine.

y = 50

y = 40

BitmapData stores the bitmap data. It doesn t give you direct access to the pixels in memory,

efficient implementations, the required expertise and effort makes this approach insufficient for developing sophisticated application behaviors for largescale sensor networks. The concept of a logical neighborhood-defined in terms of distance, hops, or other attributes-is common in node-centric programming. Common operations upon the logical neighborhood include gathering data from all neighbors, disseminating data to all neighbors, applying a computational transform to specific values stored in the neighbors, etc. The usefulness and ubiquity of neighborhood creation and maintenance has motivated the design of node-level libraries [56, 551 that handle the low level details of control and coordination and provide a neighborhood API to the programmer. Middleware services [26, 37, 621 also increase the level of programming abstraction by providing facilities such as phenomenon-centric abstractions. Middleware services could create virtual topologies such as meshes and trees in the network, allow the program to address other nodes in terms of logical, dynamic relationships such as leader-follower or parent-child, support statecentric programming models [35], etc. The middleware protocols themselves

y = 10

BitmapData objects can be transparent or discard alpha channel information. Set this with the transparent property. BitmapData objects are xed in size at construction time.

y = 20

Bitmap data takes up memory. When releasing BitmapData instances, call dispose() on them to manually dispose the internal bitmap data.

14-14

Bitmaps may be smoothly interpolated if the Bitmap s smoothing property is set to true. If false, stage quality settings have no effect on their appearance.

y increases most rapidly. This direction is normal to the tted response surface contours. We usually take as the path of steepest ascent the line through the center of the region of interest and normal to the tted surface contours. Thus, the steps along the path are proportional to the regression coef cients 5 i 6 . The experimenter determines the actual step size based on process knowledge or other practical considerations. Experiments are conducted along the path of steepest ascent until no further increase in response is observed. Then a new rst-order model may be t, a new direction of steepest ascent determined, and further experiments conducted in that direction until the experimenter feels that the process is near the optimum.

160.0 41.50 158.3 41.00

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