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A LAN is exactly what the name implies: A physically small network, typically characterized by high-speed transport, low error rate, and private ownership, which serves the data transport needs of a geographically small community of users. Most LANs provide connectivity, resource sharing, and transport services within a single building, although they can operate within the confines of multiple buildings on a campus. When LANs were first created, the idea was to design a network option that would provide a low-cost solution for transport. Up until their arrival, the only transport option available was dedicated private line from the telephone company or X.25 packet switching. Both were expensive, and X.25 was less reliable than was desired. Furthermore, the devices being connected together were relatively low-cost devices; it simply didn t make sense to interconnect them with expensive network resources. That would defeat the purpose of the LAN concept. All LANs, regardless of the access mechanism, share certain characteristics. They all rely on some form of transmission medium that is shared among all the users on the LAN; all use some kind of interrupt and contention protocol to ensure that all devices get an equal opportu-



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Figure 6-22. Relationship diagram of Books and BookDetails tables of the ApressBooks database Next add a new item ADO.NET Entity Data Model to your WCFDataServiceDemo.Web project and name it to DataModel.edmx, as shown in Figure 6-23.

Downloaded from Digital Engineering Library @ McGraw-Hill (www.digitalengineeringlibrary.com) Copyright 2004 The McGraw-Hill Companies. All rights reserved. Any use is subject to the Terms of Use as given at the website.





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This kind of data error, if not detected and eliminated, can skew the results produced by almost any mechanical trading model Although anything but innocuous, such errors are obvious, are easy to detect (even automatically), and are readily corrected or otherwise handled More innocuous, albeit less obvious and harder to find, are the common, small errors in the settling price, and other numbers reported by the exchanges, that are frequently passed on to the consumer by the data vendor Better data vendors repeatedly check their data and post corrections as such errors are detected For example, on an almost daily basis, Pinnacle Data posts error corrections that are handled automatically by its software Many of these common, small errors are not seriously damaging to software-based trading simulations, but one never knows for sure.

Downloaded from Digital Engineering Library @ McGraw-Hill (www.digitalengineeringlibrary.com) Copyright 2004 The McGraw-Hill Companies. All rights reserved. Any use is subject to the Terms of Use as given at the website.

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Depending on the sensitivity of the trading or forecasting model being analyzed, and on such other factors as the availability of data-checking software, it may be worthwhile to run miscellaneous statistical scans to highlight suspicious data points There are many ways to flag these data points, or ourlieru, as they are sometimes referred to by statisticians Missing, extra, and logically inconsistent data points are also occasionally seen; they should be noted and corrected As an example of data checking, two data sets were run through a utility program that scans for missing data points, outliers, and logical inconsistencies The results appear in Tables I-1 and 1-2, respectively Table I 1 shows the output produced by the data-checking program when it was used on Pinnacle Data Corporation s (800-724-4903) end-of-day, continuous-contract data for the S&P 500 futures.

2

ASCII codeset is shown in Table 2-1. Mainframes, however, use a different codeset called the Extended Binary Coded Decimal Interchange Code (EBCDIC); the ASCII traffic must be converted to EBCDIC if the mainframe is to understand it, and vice versa, as shown in Figure 2-4.

As you press Add, the Entity Data Model Wizard will appear. I will list settings/values for each screen of the wizard along with the title of the wizard steps: 1. 2. Choose Model Content: Select Generate from Database Choose Your Data Connection: Here create a new connection for the ApressBooks database. Name this connection setting ApressBooksEntities in the text box at bottom of this wizard screen.

The utility found no illogical prices or volumes in this data set; there were no observed instances of a high that wan less than the close, a low that was greater than the open, a volume that was less than zero, or of any cognate data faux pas Rvo data points (bars) with suspiciously high ranges, however, were noted by the software: One bar with unusual range occurred on 1 O/l 9/87 (or 871019 in the report) The other was dated 10/13/89 The abnormal range observed on 10/19/87 does not reflect an error, just tbe normal volatility associated with a major crash like that of Black Monday; nor is a data error responsible for the aberrant range seen on 10/13/89, which appeared due to the so-called anniversary effect Since these statistically aberrant data points were not errors, corrections were unnecessary..

ASCII Value 0110000 0110001 0110010 0110011 0110100 0110101 0110110 0110111 0111000 0111001 1000001 1000010 1000011 1000100 1000101 1000110 1000111

Downloaded from Digital Engineering Library @ McGraw-Hill (www.digitalengineeringlibrary.com) Copyright 2004 The McGraw-Hill Companies. All rights reserved. Any use is subject to the Terms of Use as given at the website.

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