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keytool -export -alias <key_alias> -file <output_filename>cer. QR Code ISO .keystore Click OK to use the speci ed keystore To create a new policy, click the Add Policy Entry button in the Policy Tool dialog box (see Figure 8-8) The Policy Entry window (Figure 8-10) will be displayed In the CodeBase text box, enter the URL to the codebase for your applet In the SignedBy text box, enter the alias for your certi cate Then click Add Permission to de ne the permissions for connecting to the LDAP server The Permissions dialog box (Figure 8-11) will be displayed In the Permissions combo box, choose SocketPermission In the Target Name text box, enter the host name of the LDAP server In the ctions combo box, choose connect Click OK to add the permissions Figure 8-12 shows what the Policy Entry dialog box looks like after the socket permission has been added. Draw Barcode In Java Using Barcode drawer for Java .Related: Intelligent Mail Generator .NET WinForms , Code 39 Generating ASP.NET , Intelligent Mail Generator C#

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between folders in the library, but you can export and import into a new location To export a task, select the task and select the Export option from the Action menu, which prompts for an XML to which to save the task con guration To import a task, select the folder to import to and select Import Task from the Action menu The XML le is prompted for, and once selected, the XML is opened and a properties dialog showing all the con gurations from the le is shown, allowing changes if required; then the task is saved Select a task, and you can force it to run immediately if that option was enabled in the Settings, to allow execution on-demand via the Run action In addition, you can stop a running task via the End action There will be times you have tasks that you want to stop executing for a period of time but don t want to export or delete o stop execution, simply select the Disable action for a task, and when you are ready to enable it again, select Enable from the action menu. 17 MANAGING AND MAINTAINING WINDOWS SERVER 2008. Generate European . Draw Barcode In VS .NET Using Barcode maker for .NET .Related: Code 39 Generating Excel , Print UPC-A ASP.NET , Make Interleaved 2 of 5 Excel

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FIGURE 4-28 Modifying a setting in the security database Figure 4-29 provides a quick recap about how core the security database is Note that the security database is maintained in the le you speci ed, so if you close the Security Con guration and Analysis snap-in, you can open an existing security database (sdb le) to once again see all the settings con gured in the database in addition to the data gathered from the server that was nalyzed. GS1 - 13 Encoder In .NET Using Barcode maker for ASP . Integration with Group Policy. Draw USS Code 39 In .Related: PDF417 Generation ASP.NET , Generate EAN-13 Word , Word Code 128 Generating

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the Publishing API, deployment options, site configuration, and template development A The length of time SDM takes to run depends entirely on the number and size of the objects it has to expor running example is used throughout the book to illustrate how important CMS features are your site is mostly HTML, is relatively flat, and doesn't have too many postings and/or resources, SDM coul implemented in real-world Web site development Inside you'll find answers to such questions done in a matter of seconds If your site is very large, has a complex channel structure, and/or has lots of b as: files, SDM may take longer to run Once SDM finishes, you'll end up with one SDO file, which you can trans the other implementation of CMS to import In Figure 21-5, we've provided a screen shot of one portion of export report for How BOTS export exercise As you can see, the report shows not only the channels, but th 6: our do you customize workflow postings it exported 10: How do you develop for Microsoft Content Management Server (CMS) 2002 sing Visual Studio NET Figure 21-5 The SDM export report 17: How do you establish user rights 22: How do you best deploy CMS according to your organization's needs, size, and resources 32: How do you publish dynamic data . NET Figure 21-5 The SDM export report 17 . Draw Barcode In .NET Using Barcode creator for .NET .Related: Create EAN 128 Java , Print UPC-A VB.NET , Code 39 Generating .NET

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The COM interface is broken into two parts client and server and then two subcomponents import and export Both the How do you customize workflow the same from a functionality standpoint The server o 6: client and the server interfaces are set is used to act on a local machine, and the client object is used for performing import or export tasks remotely For 10: How do you were creating an export package on a source server, you'd use the server example, if you develop for Microsoft Content Management Server (CMS) 2002 components Once you've created the SDO package on the source server using the server component, you using Visual Studio NET would transfer the SDO to the destination and use the client component on the source server to start a rem 17: the do you establish user rights import process on How destination In our examples, we're going to use the server object to export a packag and then use the client object to perform the import Both the server and the lient deployment objects hav 22: properties best deploy CMS according to your organization's needs, size, virtually the same How do youand methods and resources . Draw EAN-13 In .NET Using Barcode encoder for .Related: Creating EAN-8 Excel , PDF417 Generation VB.NET , ASP.NET QR Code Generation

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the differences in the forecast generated by the combined set (containing total of 100 examples) and the forecast generated by 50 ef cient and 50 inef cient cases Based on the results plotted in Figure 312, it can be seen that the difference between the combined forecast and the forecast generated by learning from ef cient cases is lower (RMS error 00245) than the difference between the combined forecast and the inef cient forecast (RMS 00667) This shows that for larger data sets, ANNs have a tendency to learn patterns from ef cient cases Inef cient cases in the training set lead to poor forecasting accuracy, hurt the monotonicity assumption, and foster inconsistent learning Among the key issues in the DEA assessment of technical ef ciency are: 1 Comparison of sets of DMUs that perform uniform operations 2 Assumption that, for ef cient DMUs, higher values of input should lead to higher values of output 3 No assumption made concerning the functional form that links the inputs and outputs The following are similarities between ANNs and DEA models: 1 DEA and ANNs are nonparametric models 2 Neither DEA nor ANNs make assumptions about the functional form that links its inputs to outputs 3 DEA seeks a set of weights to maximize the technical ef ciency, whereas ANNs seek a set of weights to derive the best possible t through observations of the training data set In the case of using DEA for preprocessing data for ANNs, DEA eliminates some of the inconsistencies in the data that may hurt the monotonicity assumption For example, if the training data set consists of two examples with the same inputs but different outputs, the example with a lower output receives a lower technical ef ciency The lower technical ef ciency increases the likelihood of elimination of the case with the lower ef ciency For a slight difference in outputs, the difference in ef ciency between the two examples may be low and both examples may be included in the training data However, for large differences in outputs, the case with a lower ef ciency may clearly be considered as an outlier (as this may hurt the monotonicity assumption) and has a higher likelihood of elimination from the ef cient training data Whether or not the low ef ciency case is nally eliminated from the ef cient data set depends on its actual ef ciency, number of total examples, and number of inputs, among other things The possibility of eliminating a low ef ciency case the from training data set is important when two examples show inconsistency; keeping both examples in the raining data set would impair the ANN learning Because ANN learning is through nonparametric regression-type learning of a nonlinear curve, outliers and inconsistent data impair its learning DEA models, on the.

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