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Homeland Security awards 2 grants to Rutgers for nuclear threat detection
Date:9/17/2007

athematics, computer science, statistics and engineering at Rutgers and two DyDAn partner institutions, Princeton University and Texas State University at San Marcos. The university researchers also will collaborate with scientists at three national research laboratories, Los Alamos, Pacific Northwest and Sandia. Roberts is the principal investigator. First-year funding is $485,767, with $2 million expected over four years.

Sensor management is challenging due to the variety of potential settings for sensor networks, such as seaports, land border crossings, major metropolitan traffic arteries and stadiums. Containers coming off ships and trucks crossing borders, for example, can be directed through scanning devices, but vehicles on bridges or in tunnels need to be examined while moving and tracked if suspicious. Container shipments can receive a quick initial scan, but the readings have to be analyzed quickly and reliably to determine if further examination is warranted. The alternative a detailed inspection of each shipment would quickly choke port traffic. At high-visibility events such as Olympic Games or football championships, temporary sensors could be deployed around stadiums and networked for the duration of the event.

Sensors in such environments also have to distinguish readings caused by legitimate nuclear sources, such as smoke detector shipments or people who have undergone medical tests or treatments, from readings caused by true threats. The second project aims to optimize the value of sensor information to clarify ambiguous or deceptive readings. It will involve faculty from Rutgers SCILS and RUTCOR. Paul Kantor, a professor in SCILS and director of the Center for Interdisciplinary Studies in Privacy and Security, is the principal investigator. First-year funding is $145,742, with $290,000 expected over two years.

Both projects will promote a well-planned defense against illicit nuclear materials with the least possible
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Contact: Carl Blesch
cblesch@ur.rutgers.edu
732-932-7084 x616
Rutgers, the State University of New Jersey
Source:Eurekalert

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