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In Bianco et al. (2001), the authors present the Sensor Location Problem: that of locating the minimum number of traffic sensors at intersections of a road network such that the traffic flow on the entire network can be determined. They offer a necessary and sufficient condition on the set of monitored nodes in order for the flow everywhere to be determined. In this paper, we present a counterexample that demonstrates that the condition is not actually sufficient (though it is still necessary). We present a stronger necessary condition for flow calculability, and show that it is a sufficient condition in a large class of graphs in which a particular subgraph is a tree. Many typical road networks are included in this category, and we show how our condition can be used to inform traffic sensor placement.

With a simple mathematical model, we explored the antiterrorist effectiveness of airport passenger prescreening systems. Supporters of these systems often emphasize the need to identify the most suspicious passengers, but they ignore the point that such identification does little good unless dangerous items can actually be detected. Critics often focus on terrorists’ ability to probe the system and thereby thwart it, but ignore the possibility that the very act of probing can deter attempts at sabotage that would have succeeded. Using the model to make some preliminary assessments about security policy, we find that an improved baseline level of screening for all passengers might lower the likelihood of attack more than would improved profiling of high-risk passengers.

Abstract-We consider the problem of cooperative search using autonomous aquatic vehicles, giving a proof-of-concept demonstration in an aquatic testbed. We implement a point-topoint controller for remote-controlled submarines with severe control and buoyancy limitations, develop software to track their motion and establish reliable communication and control. We then propose multiple randomized algorithms, based on Lévy flights, for locating sparse targets in a three-dimensional bounded environment. These algorithms are tested in simulation, showing that they are competitive with nonrandom systematic search, while likely also more robust. The simulations are combined with in-tank tests to display performance under real physical conditions.

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