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There is clearly a perceptual difference between the characteristics of these two forms of audio recording and playback; whether this difference is signi cant enough to seriously affect the enjoyment of recorded music is part of the running debate The same engineers who wrestled with the issues surrounding the digital storage of music began to adapt the storage techniques so that they could be applied to data One of the most signi cant problems was the approach to error correction and data integrity The correction codes required on a music CD are minimal If a disc gets scratched and several hundred bits become unreadable, the playback units can extrapolate from the surrounding data and basically ll in the missing information so that there are no audible artifacts Computer data is not so forgiving.

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Enclosing character constants in single quotes works for most printing characters, but a few characters, such as the carriage return, pose a special problem when a text editor is used. In addition, certain other characters, such as single and double quotes, have special meaning in C#, so you cannot use them directly. For these reasons, C# provides special escape sequences, shown in Table 2-2. These sequences are used in place of the characters that they represent. For example, this assigns ch the tab character:

A single byte missing from an application program could make the program unusable, so preventing any data loss becomes absolutely critical to the usefulness of the medium The solution would require a new format with expanded codes that could protect data integrity more effectively..

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This is a Windows-generated error, indicating that no printer has been installed or that Windows has not been informed of a default printer to use. As well as running the

When using the TPL, there are two basic ways in which you can add parallelism to a program. The first is called data parallelism. With this approach, one operation on a collection of data is broken into two or more concurrent threads of execution, each operating on a portion of the data. For example, if a transformation is applied to each element in an array, then through the use of data parallelism, it is possible for two or more threads to be operating on different ranges of the array concurrently. As you can imagine, such parallel actions could result in substantial increases in speed over a strictly sequential approach. Although data parallelism has always been possible by using the Thread class, it was difficult and time-consuming to construct scalable solutions. The TPL changes this. With the TPL, scalable data parallelism is easy to add to your program. The second way to add parallelism is through the use of task parallelism. This approach executes two or more operations concurrently. Thus, task parallelism is the type of parallelism that has been accomplished in the past via the Thread class. The advantages that the TPL adds are ease-of-use and the ability to automatically scale execution to multiple processors.

Unlike transmit load balancing, you can configure Fast Ether Channel (FEC) to increase both transmitting and receiving channels between the server and switch. For example, an FEC team containing two Fast Ethernet adapters configured for full-duplex operation provides an aggregate maximum transmit rate of 200 Mbps and an aggregate maximum receive rate of 200 Mbps, resulting in a total bandwidth of 400 Mbps. All adapters are configured for transmit and receive, with the load spread roughly equal. FEC works only with FEC-enabled switches. The FEC software continuously analyzes load on each adapter and balances network traffic across the adapters as needed. Adapter teams configured for FEC not only provide additional throughput and redundancy, but also provide the benefits of Network Fault Tolerance (NFT). The switch ports should also be manually configured to support this configuration, so autosensed aggregation does not occur. For more information, please see Citrix Knowledge Base article CTX434260 and/or contact your hardware vendor.

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