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With the evolution of the competitors,AMD and Cyrix brought out their own versions of their processors instead of pure clones (copies). The Cyrix 5x86 belongs to this generation.

6. View the contents of the /etc/motd and /etc/passwd files. Use the cat, more, and less commands to see how each command handles the output. The /etc/motd file contains the message of the day (what you see after you first log in). The /etc/passwd file contains a list of all the users who are authorized to use the system.

The newest version of Solaris Operating Environment is 9.0, which was launched by Sun in the summer of 2002. Interestingly, this new version of Solaris provides traditional OS functionality plus application and directory management services, that is, Sun bundles the Sun ONE Application Server and Sun ONE Directory Server along with Solaris 9.0. Apart from this, Solaris 9 OE also carries enhancements in the areas of scalability, availability, manageability, and security. Also, the earlier versions of Solaris OE are available.

Note that the first line of this example identifies the service as rsync. This exactly matches the service name listed in the /etc/services file, causing the service to

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Managing credit risk: Financial institutions continually receive applications for loans, credit cards, and so on They need to make a timely risk assessment on whether to provide these services to an applicant and under what terms Standard credit scores are available based on credit histories; however, additional models are often generated that provide a higher degree of accuracy These new models are often tailored to an individual product In addition, customers are often segmented into groups, using clustering methods and speci c credit assessment models generated for these typical and atypical groups Models of credit risk are often built using methods such as logistic regression, decision trees, or neural networks These types of models can be used during both the application process and the collection process.

These models are often built under a general assumption, such as the current condition of the economy, and may need to be rebuilt should any of these assumptions change Section 55 provides a case study to illustrate this scenario Identifying suspicious activity: Detecting credit card fraud is a major challenge and various analytical approaches have been used to identify and circumvent this suspicious activity Predictive models are built from historical transaction data including both fraudulent and nonfraudulent transactions, selecting observations with a balance of the two cases Models are often built that maximize accuracy, and a level of false positives is tolerated This is because, overall, the institutions wish to be able to identify as much fraudulent activity as possible Models for other suspicious activities are also built and are used to detect criminal activities such as money laundering.

Mining trading data: Data mining approaches, such as predictive analytics, are often applied to nancial market data Generating models and understanding trends in the nancial markets are important tools to optimize investment pro ts These data mining approaches are used to predict when to buy and sell stocks, and other investments Multidimensional time series data sets are often used to build these prediction models The data contains lots of noise and is invariably linked to major news events, which are sometimes even built into the model Many different data mining approaches have been applied to this problem Neural networks are extensively used since they handle the inherent noise in the data well Although predictions over the long term are extremely dif cult, predictions for short-term events are common However, the usefulness of these models is often short-lived, and they need to be retrained constantly to provide effective predictions.

Laws and regulations around electronic data have created quite a stir. Companies and agencies are scrambling to become compliant . Compliancy requirements have hit several areas of data management around

In addition to predicting individual stock prices, data mining methods are used to assess portfolios of products, selecting optimal combinations..

31. If you have time and there are other users, then practice sending mail to someone who is logged into your system. Otherwise, log out from the system.

10 6

We annualize tracking risk by multiplying it by the square root of the number of periodic return observations in a year.

FIGURE 12-8 Pattern of space tapered arrays using 90 beamwidth elements: 32 elements (solid); 24 elements (dashed).

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