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The following data validation formula allows the user to enter a value only if it s greater than the value in the cell directly above it:
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The Struts servlet uses the action mappings to determine how to handle a request. In the example above, the Struts servlet will handle a request for the URL ending with oldfriends.do by:
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The local oscillators used in converters can be driven either by a pilot crystal oscillator or by a frequency synthesizer. In the first case, changing the frequency requires replacement of the crystal (or switching between multiple crystals). In the second case, changing the frequency can be effected very simply by thumbwheels or even by remote control. The required frequency stability (long term) may range from some 10 5 (FDM-FM and TV) to 3 10 8 (SCPC). Local oscillators must feature low phase noise at baseband signal frequencies in order to comply with the general requirements on earth-station equipment noise (see 7.5.3.1). It should be noted that both low phase noise requirements and frequency stability requirements are specially stringent in the case of SCPC transmission and reception. High performance crystal controlled oscillators or frequency synthesizers must be used in this case.
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This formula works well, but setting it up can be confusing. The formula actually counts the number of cells that are less than or equal to 12 and then subtracts the number of cells that are less than 6. The following COUNTBETWEEN function is essentially a wrapper for this type of formula:
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Understanding the basics of Web services architecture Key architectural requirements and constraints Building blocks of Web services architecture The role of Web services standards and technologies Web services communication models How to implement Web services How to develop a Web services provider environment using J2EE How to develop a client service requester environment
a subset of variables over the same ve observations as Table 3.5. This table is limited to six normalized variables (income, age, children, electronic, groceries, and clothes). Distance measures compute a number for any pair of observations. These measures compare the values for each of the variables in the two observations and compute a distance based on some function relating to the differences between these values. The following describes a number of distance measures. Euclidean The euclidean distance is one of the most common distance functions. If a data set only has two variables, then the euclidean distance would calculate the physical distance between the two points plotted on a scatterplot. The following formula calculates a euclidean distance between two observations ( p and q), measured over n variables: n Xq ( pi qi )2 dp,q
So we could refer to the change in market prices to calculate the returns to securities held in the portfolio, in some cases. However, returns calculated in this manner have a built-in assumption that there was no trading of the security or income earned by the security for the day. We can see this assumption by way of an example. Say that the price of our stock increased steadily through the day, from 10 to 11. And instead of holding the stock at the beginning of the day, we purchased the stock during the day. If we bought the stock at mid-day for 10.50, our dollar gain would have been only 50 cents per share, not $1.00. So our return would only be 4.76% ((11.00/10.50) 1). If we had used the daily price change to calculate the return, the reported return to the fund would be misleadingly high. If we bought the security in multiple lots through the day, all at different prices, we would nd it easiest to calculate our return by taking the market value of the position at the end of the day (shares end of day price) and dividing it by the sum of the net amounts of the individual stock trades. The difference between our two returns, 10% and 4.76%, re ects the trading done in the portfolio. Sometimes the return calculated without the effect of trading, in this case the 10% return, is called a price-to-price return or a buy-and-hold return. Buy-and-hold returns might approximate the actual return earned to the security by the fund, but depending on the type of portfolio, amount of turnover and volatility experienced, the differences can be large. The implication of portfolio trading is that if we want to calculate the true fund-speci c return earned on a security, we have to calculate the security level returns for each fund independently. Thus, performance measurement at the security level requires more work to implement than many portfolio management functions, for example, calculating the duration or the P/E ratio for each security held within a fund (since these values are the same for every portfolio holding that security). Exhibit 15.1 shows the difference between the single period price-to-price return and the actual total return, which includes the effect of trading.
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