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1. To mitigate the effects of multipath propagation, we can use an equalizer at the RX. A simple example of an equalizer is the linear zero-forcing equalizer. Noise enhancement is, however, one of the drawbacks to this type of equalizer. Explain the mechanism behind noise enhancement and name an equalizer type where this is less pronounced.
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A traditional use of data mining is to train a data mining model using data for which an outcome is already known and then use that model to predict the outcome of new data as it becomes available. This use of data mining requires that several steps be performed, only some of which happen within Analysis Services: Business and Data Understanding: Understand the questions that are important and the data available to answer those questions. Insights gained must be relevant to business goals to be of use. Data must be of acceptable quality and relevance to obtain reliable answers. Prepare Data: The effort to get data ready for mining can range from simple to painstaking depending upon the situation. Some of the tasks to consider include the following: Eliminate rows of low data quality. Here the measure of quality is domain specific, but it may include too small an underlying sample size, values outside of expected norms, or failing any test that proves the row describes an impossible or highly improbable case. General cleaning. Eliminate duplicates, invalid values, inconsistent values, scaling, formatting, etc. Analysis Services accepts a single primary case table, and optionally one or more child nested tables. If the source data is spread among several tables, denormalization by creating views or preprocessing will be required. Erratic time series data may benefit from smoothing. Derived attributes can be useful in the modeling process, typically either calculating a value from other attributes (e.g., Profit=Income-Cost) or simplifying the range of a complex domain (e.g., mapping numeric survey responses to High, Medium, or Low). Some types of preparation can be accomplished within the Analysis Services data source view using named queries and named calculations. When possible, this is highly recommended as it avoids reprocessing data sets if changes become necessary. Finally, it is necessary to split the prepared data into two data sets: a training data set that is used to set up the model, and a testing data set that is used to evaluate the model s accuracy. The Integration Services Row Sampling and Percentage Sampling transforms are useful to randomly split data, typically saving 10 to 20 percent of rows for testing. Model: Analysis Services models are built by first defining a data mining structure that specifies the tables to be used as input. Then data mining models (different algorithms) are added to the structure. Finally, all the models within the structure are trained simultaneously using the training data. Evaluate: Evaluating the accuracy and usefulness of the candidate mining models is simplified by Analysis Services Mining Accuracy Chart. Use the testing data set to understand the expected accuracy of each model and compare it to business needs.
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Figure 11.11. Set the hours of availability for your printer.
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A group is nothing more than a container for managing user accounts. The most important aspect of a group, however, is that you can assign permissions to it, rather than grant permissions to individual users. You rarely need to create a user who is so peculiar to an organization that she has rights and access to resources that no one else has. Even the Administrator account, of which you have only one, is placed into several groups to gain access to sensitive resources and information. Windows 2008 groups come in two avors: security group and distribution group: Security group. This is the standard Windows Server 2008 security principal, stored as an entry in the ACL. Security groups, however, can now be mailed to. In other words, all the members in the security group who have an e-mail address stored in their User account objects can receive e-mail. Distribution group. This group is not a security principal and is used only as a distribution list. You can store contacts and user accounts in the distribution group. Because contacts do not contain the overhead of user accounts, including contacts only in large groups makes more sense. This group is also compatible with Microsoft Exchange and can play a large part in your telephony and messaging applications as well. After you upgrade Exchange to support Active Directory, you can eliminate the Exchange distribution lists and reduce the administrative burden on the e-mail administrators. Note that this applies to pre-2000 versions of Exchange Server because latter versions integrate AD support.
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