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Some attributes take numbers as their values. In some cases, the numbers can be either a set number (usually of pixels, which are just the dots on your screen comparable to dpi, the measurement for dots on your printer) or a percentage. For example, when you define a table, you may want the first column to be 25 percent of the screen width, the second column to be 50 percent of the screen width, and the third column to be 25 percent of the screen width. Regardless of how the screen is sized, it changes size to fit in proportionately. If you were to assume the screen was 636 pixels and divide it yourself, the last column of the table may not be visible if the visitor to your page didn t have the browser open in full-screen mode. For a form, however, when you indicate the size (one of the attributes for text fields) of a field, you are indicating the number of characters. For an image, when you indicate the width (one of the attributes for object elements), you are indicating the number of pixels.
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the alcoholic beverage sales in the coffee shop and dining room, as well as in the lounge. You are referred to the relevant section in 9 for forecasting beverage sales. Assume that total annual beverage sales for the proposed hotel have been calculated and are estimated to be $1,038,000. Combined food and beverage sales will be $2,608,000. From the combined food and beverage sales figures, the direct operating costs must be deducted. As was the case with the rooms department, these costs can be estimated as a percentage of sales, using national restaurant industry figures for this size and type of operation, adjusting if necessary for local conditions. The departmental income statement can now be prepared. Food Sales revenue Cost of sales Gross profit Payroll and related expenses Other direct operating expenses Net departmental operating income $1,570,000 ( 628,000) $ 942,000 Beverage $1,038,000 ( 261,000) $ 777,000 $921,000 519,000 Total $2,608,000 ( 889,000) $1,719,000 ( 1,440,000) $ 279,000
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These assumptions allow maximum 14.4 MB (megabytes) of data per subscriber per day, which is equivalent to 430 MB per subscriber per month. A similar calculation for voice shows that 2500 min of mobile-to- xed voice per subscriber can be
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The assistant sales manager has left a message for the front of ce manager and the food and beverage manager requesting clearance to book a conference of 400 accountants for the rst three days of April. The front of ce manager needs to check out some things before returning the call to the assistant sales manager.
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The 71 variables listed in Figure 7.25 The clusters uncovered by the BIRCH two-step algorithm.
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initiation of chondrogenesis in this system, withdrawal of dexamethasone from the culture after 7 days promotes greater extracellular matrix production [Roh et al., 2001]. Regardless of the exact composition of the inductive medium, the cartilage produced in this manner is probably best described as a brocartilage, because there is type I collagen produced at all times during the culture. Clearly, the center of a pellet is more hyaline and the outer layers are more brous (Fig. 4.5, See Color Plate 3), but this method does not produce a cartilage that is identical to any of the cartilages found in the body, which have individual features based on their extracellular composition and organization. One other feature of the system that should also be noted is the progression of the cells through chondrogenesis to become hypertrophic chondrocytes, expressing type X collagen, that will die by apoptosis [Johnstone et al., 2002]. Although a good feature of the system for exploring differentiation, the production of hypertrophic cartilage is not necessarily desired, depending on the type of cartilage that is the repair goal. This aspect is discussed further in Section 6.
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meq/L Per cent 4.24 2.88 11.74 0.15 7.84 0.60 10.89 22.3 15.2 61.8 2.8 40.6 3.1 56.3
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2.1 For the triple repetition block code Cb (3, 1) generated by using the parity check submatrix P = [1 1], construct the table of all the possible received vectors and calculate the corresponding syndrome vectors S = r HT to determine correctable and detectable error patterns, according to the error-correction capability of the code. 2.2 The minimum Hamming distance of a block code is dmin = 11. Determine the error-correction and error-detection capability of this code. 2.3 (a) Determine the minimum Hamming distance of a code of code length n that should detect up to six errors and correct up to four errors per code vector, in a transmission over a BSC. (b) If the same block code is used on a binary erasure channel, how many erasures in a block can it detect, and how many can it correct (c) What is the minimum block length that a code with this minimum Hamming distance can have
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Your MBE server will begin the process of pulling down channel guide metadata from the Video Source(s) you specified earlier during the backend configuration process. All this takes is a simple command-line invocation:
sizes under 2,500. Finally, the scaled ML performed about the same as the ML and GLS estimators and better than the ADF estimator at all but the largest sample sizes. (This is interesting in that the ADF estimator has no distributional assumptions and, theoretically, should perform quite well under conditions of nonnormality.) With small samples sizes the Yuan-Bentler test statistic performed best. Estimation Methods and Dependence The assumption that errors are independent underlies SEM and other multivariate techniques. Hu et al. also investigated estimation methods and test statistic performance when the errors and factors were dependent but uncorrelated. Factors were dependent but uncorrelated by creating a curvilinear relationship between the factors and the errors. Correlation coef cients examine only linear relationships; therefore, although the correlation is zero between factors and errors, they are dependent. ML and GLS performed poorly, always rejecting the true model. ADF was poor unless the sample size was greater than 2,500. EDT was better than ML, GLS, and ADF but still rejected too many true models. The scaled ML was better than the ADF estimator at all but the largest sample sizes. The scaled ML performed best overall with medium to larger samples sizes, and the Yuan-Bentler performed best with small samples. Some Recommendations for Choice of Estimation Method/Test Statistic Sample size and plausibility of the normality and independence assumptions need to be considered in selection of the appropriate estimation technique. ML, Scaled ML, or GLS estimators may be good choices with medium to large samples and evidence of the plausibility of the normality assumptions. The independence assumption cannot be routinely evaluated. The Scaled ML is fairly computer intensive. Therefore, if time or cost is an issue, ML and GLS are better choices when the assumptions seem plausible. ML estimation is currently the most frequently used estimation method in SEM. In medium to large samples the scaled ML test statistic is a good choice with nonnormality or suspected dependence among factors and errors. In small samples with nonnormality the Yuan-Bentler test statistic seems best. The test statistic based on the ADF estimator (without adjustment) seems like a poor choice under all conditions unless the sample size is very large (>2,500). Similar conclusions were found in studies by Fouladi (2000), Hoogland (1999), and Satorra (1992).
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