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The Virginia Beach Police Department, the state s third-largest law enforcement organization, tries to maintain a high level of security and safety, particularly given the city s status as a popular tourist site To that end, the department was interested in deploying a facial recognition system to determine the technology s value as a public safety tool When the proposal to install a facial recognition system was introduced, however, controversy ensued Citizen involvement, therefore, became an important factor in evaluating the acceptability of the technology City leaders organized several town meetings so that citizens questions could be answered and the public could be educated on this topic The American Civil Liberties Union (ACLU), city officials, local community leaders, and outside experts participated in these meetings A Facial Recognition Program Citizen s Advisory and Audit Committee was formed by a diverse group of citizens drawn from different organizations, including the National Association for the Advancement of Colored People (NAACP), the National Federation of Filipino Americans, the Hispanic Community Dialogue, the Virginia Beach Hotel/Motel Association, and the Council of Civic Leagues This Committee provided input and aided in preparation of a general order outlining the use and operation of the facial recognition system The Committee also serves as an auditor of the system to ensure the proper use, storage, and disposal of digital images These efforts helped win community support In August 2001, the police department applied for a Department of Criminal Justice Service grant The grant was approved for $150,000 After the city council held a public hearing, the council voted to accept the grant and appropriated an additional $50,000 for the project Virginia Beach already had a video surveillance system comprised of ten cameras in strategic locations throughout the Oceanfront area As part of the facial recognition project, the city integrated three new cameras into the existing system The facial recognition system, however, is housed on a separate, stand-alone computer to minimize unauthorized access The facial recognition system s database will contain images of subjects with warrants (for example, felony warrants, misdemeanor warrants involving violence) or reports (for example, missing persons, runaways) In addition, endangered individuals such as Alzheimer s patients will be included The chart below shows the numbers of outstanding warrants and active reports in Virginia as of September 2002:.

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A section of cable plant is shown; the resistances of cable sections and the distances between ampli ers are noted

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a measure in a grid and asking for all the records in the cube that contribute to that particular value The challenge with drilling through is that users may not understand what they are doing, and drilling through from a high level could return millions or even billions of records To prevent users from having to wait long periods of time for the data, or possibly consume the available memory on their local machine, the number of records returned for a drill through operation can be capped The default is 1000 records, although this can certainly be changed After changing any properties as desired and choosing the location of the PivotTable report from the Import Data dialog box, the PivotTable is added to the spreadsheet and the Field List window is placed on the right-hand side of the spreadsheet Figure 9-5 shows the default layout for the Field List as well as the empty PivotTable on the spreadsheet

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In 1993, the existing biometric standards were focused on the use of fingerprints that were part of the Automated Fingerprint Identification System (AFIS) for law enforcement Some of the earlier documents include the following standards:

Figure 9-5

532 V

American National Standard for Information Systems, Data Format for the Interchange of Fingerprint Information, ANSI/NIST Computer System Laboratory (CSL) 1-1993 Criminal Justice Information Services, WSQ Gray-Scale Fingerprint Image Compression Specification, 1993

484 V

In 1995, a Mugshot and Facial Image Standards Workshop was held to discuss issues related to the capture and interchange of mugshot or facial image data The workshop expanded the scope to include Scar, Mark, and Tattoo (SMT) information and agreed to expand the ANSI/NIST-CSL 1-1993 standard to include a specific logical record structure for processing mugshot, facial, and SMT image data The National Institute for Standards and Technology (NIST) revised its earlier 1993 standard and published a newer standard in 1997: American National Standard for Information Systems, Data Format for the Interchange of Fingerprint, Facial & SMT Information, ANSI/ NIST Information Technology Laboratory (ITL) 1a-1997 In September 1998, another Fingerprint Data Interchange Workshop was held that revised, redesignated, and consolidated ANSI/NIST-CSL 1-1993 and ANSI/ NIST-ITL 1a-1997 The newer standard specifies a common format to be used to exchange fingerprint, facial, scars, mark, and tattoo identification data effectively across jurisdictional lines or between dissimilar systems made by different manufacturers NIST published the document as NIST Special Publication SP 500-245 ANSI/NIST-ITL 1-2000 and NIST Special Publication SP 500-245 Over the course of the next several years, newer biometric technology became commercially available, including real-time fingerprint verification and identification, and many other biometrics, such as facial recognition, voice recognition, retinal and iris scanning, hand geometry, keystroke analysis, and many others too numerous to mention Each vendor created proprietary algorithms and unique application programming interfaces (APIs) with similar but different functions and parameters The biometric vendors soon realized this proliferation of APIs only slowed the adoption of biometric technology and a common approach was necessary, so application programmers and system integrators would only need to adopt a single API The BioAPI Consortium was formed in 1998 and published an industry specification in March 2000: BioAPI Specification, version 10, 2000