C# 3.0: A Beginner s Guide in C#

Insert Code128 in C# C# 3.0: A Beginner s Guide

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In Main( ), four delegate instances are created. One, strOp, is null. The other three refer to specific string modification methods. Next, a multicast is created that calls RemoveSpaces( ) and Reverse( ). This is accomplished via the following lines:

another person is highly intelligent while incorrectly criticizing their own intellect. These examples are actually symptoms or manifestations of projection that often hide or defend against the following deeper developmental issues for Sixes:

One other point about the preceding example. As mentioned, Sqrt( ) is a member of the Math class. Notice how Sqrt( ) is called; it is preceded by the name Math. This is similar to the way Console precedes WriteLine( ). Although not all standard methods are called by specifying their class name first, several are, as the next example shows. The following program demonstrates several of C# s trigonometric functions, which are also part of C# s math library. They also operate on double data. The program displays the sine, cosine, and tangent for the angles (measured in radians) from 0.1 to 1.0.

use the same expansion strategy that the company has used for more than eighty years to own and operate its own manufacturing facilities. A team was put together to investigate options, and after six months, it recommended three options: Athens, Georgia; a second Florida location, this one outside Jacksonville; and Bushnell, Illinois, a small town about six hours drive south of Chicago. I was told to recommend a location from a risk management perspective. I don t know which location my peers in distribution, transportation, nance, quality control, marketing, sales, and employee relations plan to recommend they have their own data and standards. But I sensed that the prevailing view among members of the executive committee is that we should go with the Florida location. We re a Florida corporation, so it s loyal to go with what we know. According to my data, however, that s not the smartest move. My recommendation that we select Georgia for the new factory location is not based on my personal preference; it s an educated opinion. My analysis is objective and comprehensive, whereas I think other departments may use more limited assessments. In my view, different risks require different methods of evaluation, and trying to use only one method of analysis may create a false sense of security. Also, for some risks, like worker comp claims, a lot of historical data exist, whereas for other risks, like those associated with building a new factory, no such data might exist. Additionally, some risks, such as fraud, can t be methodically analyzed. I have spent three months identifying which data we need to look at in order to evaluate risk properly and then researching the data. I created a weighted evaluation tool known in my industry as a stochastic simulation, and based on my analysis using this tool, it is my view that we should build our new factory in Georgia.

Note that each zone has properties that can be changed. The small down arrow next to the close button for each item in the dashboard will allow the developer to access the Edit Item dialog box for that particular scorecard or report. The Edit Item dialog lets users determine the order in which items in that zone are displayed. This is because a single zone can host more than one item. The Edit Item also lets the developer decide whether or not to cache this particular item. Caching makes sense when the underlying data does not change often or when the most up-to-date information is not critical, such as when viewing fixed date, historical data. With caching turned off, it means that each time an item is rendered, PerformancePoint Server goes back to the cube to get its data. Finally, the Edit Item dialog lets the developer set the height and width for each zone. By default, the height and width automatically adjust to fit the entire zone on the screen, but the height and width can be constrained to either a fixed number of pixels or a fixed percentage of the screen.

There s a lot of money in Vegas and that attracts people who want it. Somebody is always going to be trying to beat the house. Earl Carroll, director of surveillance at the San Remo, quoted in Technology Has Spawned a Dramatic Improvement In Casino Surveillance, Gaming Magazine, December 12, 2000. A card-counting team can take a casino for $200,000 in an hour. Robert Schmitt, CEO of Biometrica, Inc., quoted in Security Watch, May 2000. When asked why he robbed banks, career criminal Willie Sutton answered, Because that s where the money is. The criminal class that hits the nation s casinos would no doubt give a similar answer except unlike banks, casinos offer free drinks, no-cost frills, more convenient hours, and other attractions. Moreover, while Willie usually packed heat, in the form of a Thompson submachine gun You can t rob a bank on charm and personality casino thieves are usually the white collar variety who try to beat the casinos with creativity and technical gadgetry. In a given year, an estimated $40 million in illegal gains walk out the doors of Las Vegas grand casinos. Casinos want to stop this outflow. The industry has been looking to the emerging technology of facial recognition as a way to stop the hemorrhaging. Because casinos have been an early adopter of facial recognition, this chapter begins with a detailed analysis of why casinos have embraced this biometric technology. Facial recognition, though a relatively new biometric technology, has received enthusiastic acceptance by the gaming industry. In fact, many casinos were early adopters; Trump Marina, for example, installed a system in 1997 (well before facial recognition gained public notoriety in the aftermath of the Super Bowl surveillance episode in January 2001, discussed in 14). While casinos are highly secretive about their security measures, many deploy facial recognition systems. According to the International Biometric Group, a U.S. based biometric consulting firm, facial recognition is used in probably 75 percent of Las Vegas casinos to catch card counters or people who have been barred from casinos. Beverly Griffin, co-owner of Las Vegas-based Griffin Investigations, which provides security systems for casinos, estimates the penetration rate at 50 percent