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The public sector has been a major supporter, deployer, and user of various biometric technologies for years In fact, these public-sector efforts with respect to biometrics have been critical to the success of the technology as well as the biometric industry In 3, for example, Peter Higgins explained how law enforcement s need spurred research and development of large-scale automated fingerprint identification systems, like the FBI s IAFIS The examples that follow in this chapter try to capture the flavor of how the government and military are using biometrics1

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This chapter draws, in part, on the author s previous work, published in John D Woodward, Jr, Katharine W Webb, Elaine M Newton, et al, Army Biometric Applications: Identifying and Addressing Sociocultural Concerns, (RAND 2001) in Appendix B: Program Reports Julius Gatune provided valuable research assistance

A new view of the DSV showing a named query has been used to replace the product dimension snowflake tables, and a named calculation has been added as well

1 The antenna for the weakest station should occupy the topmost section of the tower 2 If the receiver signals are equal, place the highest frequency (smallest) on top so as not to weigh the top unnecessarily 3 Follow the procedures outlined for proper minimum allowed spacing Vertical separation of antennas (a)

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Currently, six states use large-scale biometric applications in social service programs: Arizona, California, Connecticut, Massachusetts, New York, and Texas Pennsylvania is considering implementing a system These various state programs all share the goal of using biometrics to prevent fraud in the form of double-dipping, or multiple enrollments, defined as having the same person enrolled in a system multiple times using multiple aliases collecting multiple payments Double-dipping can be prevented by the biometric program s capability of negative identification, or performing a one-to-many search to make certain that an individual is not already enrolled in the system By linking identity to the person s biometric, instead of the person s name, a person can only enroll in the system once because all the biometric records of those enrolled in the system will be searched for matches A new enrollee should not be in the system and when the search is done, no matches should result the identification comes back negative Although the biometric cannot prevent someone from initially enrolling in the system in an alias name, it does freeze or fix the person s identity (true name or alias name) by fixing the name to the biometric thereafter

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Top view 90-degree difference in bearing Antennas back-to-back (180 degrees apart) (b) Amin A1 0 180

mathematical calculations, or they may be used to concatenate strings For example, the fact table might store the price of the item sold as well as its cost, so a simple calculation to get the gross profit on that item could be included in the fact table in the DSV In the case of this example, the named calculation is being used for string concatenation The DimEmployee table has three columns for a person s name: FirstName, MiddleName, and LastName The named calculation shown in Figure 3-9 combines all the names into a single column called FullName The fact that FullName is a named calculation is easy to see by the small calculator icon placed next to it The DSV is very powerful Named queries can be added that, in effect, create new tables Calculations can be added to existing tables, which can speed up cube queries later because the numbers are actually materialized in the cube itself Tables in the

In California, the Los Angeles County Department of Public Social Services (DPSS) began the Automated Fingerprint Image Reporting and Match (AFIRM) biometrics program, known as LA AFIRM LA AFIRM became the grand daddy of civil AFIS welfare systems It has since been superceded by a new statewide system Owing to its grandfatherly status, it merits discussion DPSS used ink-and-paper fingerprints as early as 1986 In 1988, a steering committee approved automated fingerprint matching By 1991, DPSS launched a pilot program using automated fingerprinting By the end of 1994, the program had been deployed to 25 DPSS district offices, including 300,000 participants who must be fingerprinted These include adults receiving AFDC payments, minor parents receiving payments, and adults collecting payments for children The biometric used consists of templates made from the two index fingers DPSS made appointments for enrollment Those unable to make their appointments were given additional time to comply After that period, if an adult failed to report for an appointment, adult benefits were cut off, although children s benefits continued If an adult continued to refuse to enroll, the case was

(Antennas 0 degrees apart) 178 1 178 1 90 180 1 2

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