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Point, relates an example of just how nonintuitive the false positives problem can be. A group of military analysts had been working on a statistical method to detect car bombs in Iraq. A team of Kucik s student cadets was assigned to analyze the proposed statistical test as a nal class project. Just as with the hypothetical terrorist detector, the test was believed to accurately predict explosives when they were actually present. When the students met with the analysts who had developed the methodology, they made a case for using multiple sources of intelligence, instead of just the single test, says Kucik. They explained to the client that even with a very accurate detector, the base rate of vehicles carrying explosives is so low that when a soldier receives a positive signal, there is only a tiny chance that the vehicle is actually dangerous, Kucik continues. What seemed so powerful is that a group of undergrad students was able to share a very important (and surprising) insight with a group of PhDs and professional engineers who had spent over three years working on this problem. Greg Parnell, a full professor at West Point, with decades of experience in decision analysis, con rms that even very competent senior leaders grossly underestimate the chance of false positives. I once presented a hypothetical example to a group of high level government of cials and industry leaders in Washington, says Parnell, and they were extremely surprised when they discovered how far off their intuitive estimates were.

performance capabilities. What steps are involved when creating a new counter ________________________________________________________________________ ________________________________________________________________________ ________________________________________________________________________

Summary

basic principle, consider a simple rate-1/3 repetition code.13 The probability of a wrong decision in a coded bit is Psingle Q( ), where is the instantaneous SNR. Due to the majority rule, 2 the probability of a wrong nal decision is approximately Psingle Q2 ( ), where we have made use of the fact that the SNR of two subsequent bits is the same. Averaged over different channel states, the BER is then approximately: BER

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Before you can con gure RIP on an interface, you need to add it. In the RRAS console, open the server you want to manage and then expand the IP Routing branch. Right-click General and choose New Routing Protocol. Select RIP Version 2 for Internet Protocol from the list and choose OK. A new node labeled RIP appears under the IP Routing branch. Next, you need to specify the interface on which RIP will run, because by default no interfaces are con gured when you add RIP. Right-click RIP and choose New Interface. RRAS displays the available interfaces. Select the one on which you want to run RIP and click OK. The next step is to con gure RIP. RRAS presents a property sheet for RIP when you add the interface. You can also display the RIP properties by double-clicking the interface in the right

The SE toolkit can monitor processes, network interfaces, disks, and more. It can even monitor Web sites. The best way to become familiar with the tool (other than downloading and using it) is to read Adrian s performance column in SunWorld (www.sunworld.com). One of the specific issues to read is May 1999 (www.sunworld .com/swol-05-1999), but SunWorld has a search engine so that you can easily find other references as well. The three packages provided with the toolkit include: 1. RICHPsw, the interpreter (called SymbEL). 2. RICHPsex, the extensions package. 3. ANCrules, Adrian s rules and tools.

Once more, because you re using SESSION variables on your page, you need to begin with a call to session_start(). Then, you have your calls to a new function, setcookie(). This function creates a cookie for you, which is used to store data on the user s computer.

If we consider t)(t) to be a bandpass impulse response, then the wavelet analysis can be understood as a bandpass analysis. By varying the scaling

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