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However, various researchers have asserted that not all knowledge possessed by a team member needs to be shared by other members (Entin & Serfaty, 1999) For example, although a quarterback possesses some knowledge of receiving, this knowledge is only a subset of a receiver s knowledge of receiving Moreover, a trade-off exists in teams between specialization and generalization Thus, all team members will share general team knowledge pertaining to overall team strategies, but team members who interact more regularly than others will additionally share more specific knowledge about each others operations (CannonBowers et al, 1993; Entin & Serfaty, 1999) For example, a rugby union forward player will share general team knowledge with the back players such as knowing that the team strategy is to attack down the right wing but will share more detailed knowledge with colocated forward players.

Illustrated TCP/IP by Matthew G. Naugle Wiley Computer Publishing, John Wiley & Sons, Inc. ISBN: 0471196568 Pub Date: 11/01/98

Additional Computations:

The absolute best way to become familiar with VBA, without question, is to simply turn on the macro recorder and record some actions you make in Excel. This is a quick way to learn the relevant objects, properties, and methods for a task. It s even better if the VBA module in which the code is being recorded is visible while you re recording.

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<script language= JavaScript > <!-function MM_findObj(n, d) { //v3.0 var p,i,x; if(!d) d=document; if((p=n.indexOf( ))>0&&parent.frames.length) { d=parent.frames[n.substring(p+1)].document; n=n.substring(0,p);} if(!(x=d[n])&&d.all) x=d.all[n]; for (i=0;!x&&i<d.forms.length;i++) x=d.forms[i][n]; for(i=0;!x&&d.layers&&i<d.layers.length;i++) x=MM_findObj(n,d.layers[i].document); return x;

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wire s diameter is indicated by its gauge. Here we mean American Wire Gauge (AWG), formerly known as Brown & Sharpe (B&S). Table A.1 compares common AWG values with copper wire diameter in mm and the resistance in ohms per kilometer (Q / km).

10.2 A BRIEF REFRESHER OF PROBABILITY THEORY The main goal of this section is to review elementary probability theory results that are useful for analyzing the performance of our protocols. For a more detailed discussion of background material we refer the reader to [13]. For a random variable X, E[X] denotes the expected value of X. Let X be a random variable denoting the number of successes in n independent Bernoulli trials with para-

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dissatisfaction perceives it as a helpful emotion because this emotion helps him or her to try harder, to maintain a fighting spirit, to be better than his or her opponent, to put more effort into the game, and to be more alert Harmful effects of too much satisfaction (complacency) are reflected in being too concerned with success, not trying to play better, being too arrogant, not careful, and too risky; as result, skating becomes difficult (Hanin & Syrj , 1995, pp 180 181) A more detailed description of perceived functional effects of selected emotions across four global categories (P+, N+, P , and N ) is found elsewhere (Ruiz, 2004; Syrj , 2000) Explaining Individual Differences Numerous empirical studies revealed large interindividual variability of emotion intensity and emotion content in athletes performing similar and different sporting tasks.

Figure 6.18 Silicon germanium and silicon germanium carbon HBT TLP power-to-failure as a function of emitter width

After this, each additional bit of k reduces the set by half, and we proceed along the line of slope 1 until k = K(x n |n). For k K(x n |n), the smallest set that can be described that includes x n is the singleton {x n }, and hence Kk (x n |n) = 0. We will now illustrate the concept with a few examples. 1. Bernoulli( ) sequence. Consider a sample of length n from a Bernoulli sequence with an unknown parameter . As discussed in k Example 14.2, we can describle this sequence with nH n + 1 log n 2 bits using a two stage description where we describe k in the rst stage (using log n bits) and then describe the sequence within all sequences with k ones (using log n bits). However, we can use an k even shorter rst stage description. Instead of describing k exactly, we divide the range of k into bins and describe k only to an accu k racy of n n k n using 1 log n bits. Then we describe the actual n 2

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