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For example, Alice uses EFS on her stand-alone computer to encrypt her private files. She forgets her password but remembers the password for the built-in administrator account. She logs on as the administrator and resets the password for her account named Alice. When she resets the password, she is able to log on as Alice, but files that she encrypted as Alice are inaccessible because the master keys are inaccessible.
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The ability of the target to support the desired call mode (e.g., AMPS, CDMA, TDMA, or NAMPS). The ability of the target to support the characteristics of the MS (e.g., power class, use of discontinuous transmission). The ability of the target to support the confidentiality modes desired by the service subscriber (e.g., encryption of the radio channel).
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Magnify an area of the screen up to nine times the standard display size. Choose to have the magnified area follow the mouse pointer, the keyboard focus, the text editing focus, or any combination of these three. Invert colors for contrast. Resize and relocate the Magnifier display area.
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$sql = "INSERT INTO shoppinglist (name, qty) VALUES ($name, $qty)"; $pdo->exec($sql) or die("ERROR: " . implode(":", $pdo>errorInfo())); // close connection unset($pdo); // display success message echo 'Thank you for your submission'; } catch (Exception $e) { die("ERROR: " . $e->getMessage()); } } > </body> </html>
Table 8-4 Folder
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The empirical rule works fine as long as the distribution is approximately normal. But what do you do if the shape of the distribution is unknown or distinctly nonnormal (as, say, skewed strongly to the right) Remember that the empirical rule told you that, in a normal distribution, approximately 68% of the data are within one standard deviation of the mean, approximately 95% are within two standard deviations, and approximately 99.7% are within three standard deviations. Chebyshev s rule isn t as strong as the empirical rule, but it does provide information about the percent of terms contained in an interval about the mean for any distribution. Let k be a number of standard deviations. Then, according to Chebyshev s rule, for k > 1, 1 at least 1 2 % of the data lie within k standard deviations of the mean. For example, k 1 if k = 2.5, then Chebyshev s rule says that at least 1 2 % = 84% of the data lie with 2.5 2.5 standard deviations of the mean. If k = 3, note the difference between the empirical rule and Chebyshev s rule. The empirical rule says that approximately 99.7% of the data are within 1 three standard deviations of x . Chebyshev s says that at least 1 2 % 89% of the data 3 are within three standard deviations of x . This also illustrates what was said in the previous paragraph about the empirical rule being stronger than Chebyshev s. Note that, if at least 1 1 2 % of the data are within k standard deviations of x , it follows (algebraically) that k at most 1 % lie more than k standard deviations from x . k2
How does refactoring model methods help in improving performance 4 discussed the fat model, skinny controller approach, which proposes that business logic should be located within models, rather than controllers, wherever possible. In addition to various other benefits, following this approach can improve performance when it is used in combination with caching. As shown earlier in the section Caching Query Results, you can use caching to block the method calls on the model altogether if cached result data already exists, thereby reducing the number of lines of code that need to be executed. And fewer lines of code automatically translates to faster script parsing and execution.
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