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Things start to get a bit more complex when you have more than one hard drive in your system. As in Scenario 1, when you reach the partition screen you have to instruct Setup as to which partition you want to use for the installation. But here you have more choices because you can divide each of your drives into multiple partitions. Scenario 2 has become common in recent years as people buy inexpensive new hard drives and add them to their systems, installing Windows on the new drive after it is in place. In all cases, the new drive contains neither data nor partitions, but in many cases important data remains on the original drive. If one or more of your drives contain data that you want to keep, you must either back up the data before installing the operating system or avoid installing the OS on the partition where the data resides. To do so, make sure that you know which drive and which partition contain that data, and configure Setup to use a different drive or partition. Once you have chosen the drive that will house the installation, follow steps 3 through 10 in Scenario 1 s numbered list to partition and format the drive and install the OS. With the installation completed, load My Computer or Windows Explorer and navigate to your other drives and partitions.

With these principles in mind, the coded aperture spectrometer illustrated in Fig. 9.4 and discussed as a spectrometer in Section 9.3 and as a pushbroom imager in Section 10.6.1 is also an excellent candidate for compressive spectral imaging. To use the system as a compressive imager, one need only reinterpret Eqn. (10.63). We term instruments based on this approach as coded aperture snapshot spectral imagers (CASSIs) [88,242]. The snapshot capability, such as the ability to estimate the full spectral data cube from a single 2D frame of measurements, is the primary distinction of CASSI instruments relative to full-data-cube spectral imagers. A CASSI instrument based on the spectrograph of Fig. 9.4 is most simply described as a 2D imager in the x l plane. As discussed above, this instrument is a simple imager along the y (undispersed) axis with y image pixels mapping isomorphically to object pixels indexed by m in Eqn. (10.63). Accordingly, we focus on a 2D version of Eqn. (10.60) gn X

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Vs( s) I I(s) = sL + R = s[s L + R ]

= = = = = =

Definition A S (Sum and direct sum) Let W1 and W2 be subspaces o f a linear space V . By the sum Wl + Wz we mean the linear span o the union o W1 and W2,i.e., [Wl U Wz]. f f We say that V is a direct sum o its subspaces W , and W2 (written as V = W1@W2)if f

and therefore,

5.8 x 10

To make the determination of preferential customer selection and treatment more efficient and logical, you may want to rate your prospects and customers in different categories. Make this rating system as simple as possible. A complex system is difficult to implement, and you will spend an inordinate amount of time applying it. You should be able to determine and assign a rating to each prospect or customer in just a few minutes based upon an evaluation of their characteristics against the rating criteria you have established. Here is the simple customer and prospect rating system we use in my office: Diamond a customer who is a perfect fit for my direct mail copywriting service, meaning I have substantial experience in their industry or product, and the customer has a large volume of work, values copy and copywriters, is knowledgeable about direct marketing, and pays a premium price for premium quality.

After you click OK, the table contains the field names in the first row, the data items in the second row, and a Repeat Region wrapped around the second row, as shown in Figure 20-4.

The severity of the message is the third portion of the event log message. The severity will help you prioritize entries when reading the event log. Some event log messages are informational, while others annotate faults and warnings that have occurred. Following is a list of the severity codes for the VPN Clients event log:

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Base data type . For example, dCurrencyValue is the currency value base data type; dDecimal is the decimal base data type. The name is that of an enterprise tier artifact . For example, eVendor is the name of

We could have used single backslashes to produce the first two backslashes in the output, but the escaping is necessary at the end of the string so that the closing quote will not be escaped.

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