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communications The goal of softswitch is to bring about dissolution of this interdependent relationship where appropriate In concert with the evolution of the overall network, the softswitch concept has evolved to address a variety of network payload types More and more, telecommunications networks are utilizing IP as a fundamental protocol, particularly in the network backbone This backbone is also making VoIP services viable as an alternative to circuit-switched voice There is more to softswitch, however, than simply separating the functional components of the network Another key goal is to create an open service-creation development environment so that application developers can create universal products that can be implemented across an entire network Part of the evolution will include the development of call control models that will seamlessly support data, voice, and multimedia services We will discuss more specific examples of this functional evolution in the last section of this report.



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On-demand loading is the mechanism to load objects as they are required by the application by making separate query requests to the data source for each object. The main objective for such a mechanism is to dedicate memory resources only when necessary by loading and instantiating an object only at the point when it is absolutely needed. This approach is advisable when you need to load the data for a few entities and the volume of the data is large. To facilitate loading on demand, the DataServiceContext class has a BeginLoadProperty method, which follows the same asynchronous model where you specify the source entity, the name of the property, and a callback, as shown in the BeginLoadProperty method signature here: public IAsyncResult BeginLoadProperty( Object entity, string propertyName, AsyncCallback callback, Object state ) So let s implement this approach in our example by adding the following line of code in the BookDataGrid_SelectionChanged method. //Explicit loading (Lazy loading) using BeginLoadPropety context.BeginLoadProperty(currentBook , "BookDetails", PropertyLoadCompleted, null); The callback method PropertyLoadCompleted is as follows: private void PropertyLoadCompleted(IAsyncResult result) { context.EndLoadProperty(result); //Getting reference to current selected book Book currentBook = BookDataGrid.SelectedItem as Book; if (currentBook == null) return; var query = (from bd in currentBook.BookDetails select bd); BookDetailsDataGrid.ItemsSource = query.ToList(); } So, as per the code snippet, once the EndLoadProperty is called, the property has been properly loaded with the related entity, so we can access the related entity BookDetail through the navigation property BookDetails to bind to our BookDetailsDataGrid control.





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reward ratio improved from -0.35 to -0.17. Out-of-sample, the benefit of the genetically evolved mle-based signal exit was maintained, but not quite as dramatically. The loss on the average trade was cut from $1,135 to $990. The percentage of winning trades increased from 39 to 41%. The risk-to-reward ratio improved slightly from -0.61 to -0.60. Overall, adding the genetically evolved rule-based element to the exit strategy worked. In contrast to the neural exit, the benefit was maintained out-of-mm ple, suggesting that curve-fitting and over-optimization were not major issues. On the short side, similar benefits were observed in both samples. In-sample, the addition of the genetically evolved rule-based element reduced the loss on the average trade from a baseline of $2,084 to $1,645. The percentage of winning trades remained unchanged. Paradoxically, the annualized risk-to-reward ratio worsened somewhat, going from - 1.09 to - 1.15. Out-of-sample, the loss on the average trade dropped substantially, from $1,890 in the baseline test to $1,058, when the rule element was active. The percentage of winning trades rose from 38 to 40%, and the annualized risk-to-reward ratio improved, from - 1.02 to -0.73. Again, the addition of the genetically evolved rule-based signal exit to the MSES worked and continued to work out-of-sample.

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The result of widespread softswitch deployment will be the creation of a switching model that does not have the same restrictions that plague circuit switches, such as intelligent network triggers, application invocation mechanisms and complex service logic This functional distribution will result in faster and more-targeted feature development and delivery and significantly lower service delivery costs Softswitches will be architecturally simpler, operationally efficient, and less expensive to operate and maintain A number of corporations have now focused their efforts on the development of softswitch products Both Lucent and Nortel announced softswitch products as early as 1999 in the form of the 7R/E (Lucent) and the Succession (Nortel) Today, they have been all but abandoned because the market simply wasn t ready to bridge the gap between the circuitswitched Bellheads and the IP bit-weenies, although both companies have now come roaring back into the fray with Succession (Nortel) and iMerge (Lucent).

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