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There are certain daily usage applications, and we pay attention to the types of features that meet the needs of the user within that context So if it's horoscopes, it's usually a quick information grab, sort of an entertainment-leisure kind of activity If it's investing and it's a daily routine, there's activity associated with it, whether it be trading or portfolio analysis, and there're other dimensions to that activity that really need to be catered to or you lose the daily usage So that's one dimension The second dimension is understanding the demand on the advertising side for this particular type of user In some cases the daily user is very much in demand by the advertising community In other cases, the daily user is interesting, but isn't necessarily the premiere target demographic slice.. that an advertiser might want to reach.

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First, I spread out all my items on my staging table (see Figure 9.1). All but one of these items were acquired at garage sales for a total of $118. The large brass scale in the background was on an overstock pallet from a high-end San Francisco retailer. Its original retail was $600, and I paid $138. I hope to double my money on this.

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So, we often will measure the quality of the usage as well as frequency That stops me I have to know: "How do you quantify quality " Kris doesn't miss a beat: Quality has two primary dimensions to it The first is just the fact that the user is engaged in a type of activity that signals a purchase intent We may not know a ton about the users themselves, but if we know that they are engaged in researching or comparing two automobiles, there's a high probability that either they themselves are in a purchase process for an automobile or they're helping someone with that purchase process and can be an influencer in their purchasing decision It's an example of a quality activity that doesn't have a very high frequency but shouldn't be discounted because it's very valuable from an advertiser perspective..

Tom De Marco s Bang Metric is similar to Function Point. Bang has proven itself especially beneficial in real-time, telecommunications, and scientific software projects.

In the J2ME version, we will have to use the following statements instead:

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Bug density is measured in bugs per thousand Lines of Code (KLOC). It is the easiest metric to calculate and a critical indicator. Simply divide the number of lines of code by the number of bugs and multiply by 1,000, as in the following example.

Because the Treasury wanted all of the largest banks, regardless of nancial strength, to accept the same type of preferred stock, it had to offer attractive terms that effectively subsidized the weaker banks receiving federal assistance Another fruitful perspective on valuation is to compare the terms of the preferred stock bought by the Treasury in Goldman Sachs to the terms of the preferred stock bought by Warren Buffett in Goldman Sachs around the same time in late 2008 Consider Table 92, which summarizes ve of the key terms of both transactions Because the Treasury bought twice the amount of preferred stock as Buffett did in Goldman Sachs, the Treasury should have obtained better terms than him, but Buffett got a much better deal Buffett s initial dividend rate was 10 percent, as compared to 5 percent for the Treasury.

Flow model The ow model in WSFL speci es the execution sequence of the composed Web services and de nes the ow of control and data exchange between Web services involved. Figure 7.7 shows a ow model sample in WSFL to de ne how the two service providers can collaborate. controlLink and dataLink are used to separate data from control in service interactions.

To wrap system dialog boxes, just start the Visual Basic CCE (refer to 4 if this sounds unfamiliar to you). You ll find the entire project on the companion CD. Just open \components\ comdlg\comdlg.vbp. Too lazy to create the COM object yourself Kick back and call \install\comdlg\setup.exe.

We say a transmission line is distortionless if R/L = G/C. For this special case, Equation 3.5 yields the propagation constant = + j =

function connect() { $user = ""; $password = ""; $db = odbc_connect( 'PHPEG' , $user, $password ); if (!$db) die( "Error in odbc_connect" ); return $db; } The checkadd function extracts submitted data from the (global) $HTTP_POST_VARS