Conventional one-stop authentication of a computer terminal takes place at a user's initial sign-on. In contrast, continuous authentication protects against the case where an intruder takes over an authenticated terminal or simply has access to sign-on credentials. Behavioral biometrics has had some success in providing continuous authentication without requiring additional hardware. However, further advancement requires benchmarking existing algorithms against large, shared datasets. To this end, we provide a novel large dataset that captures not only keystrokes, but also mouse events and active programs. Our dataset is collected using passive logging software to monitor user interactions with the mouse, keyboard, and software programs. Data was collected from 103 users in a completely uncontrolled, natural setting, over a time span of 2.5 years. We apply Gunetti & Picardi's algorithm, a state-of-the-art algorithm in free text keystroke dynamics, as an initial benchmarkfor the new dataset.

We examine the problem of utilizing an autonomous underwater vehicle (AUV) to collect data from an underwater sensor network. The sensors in the network are equipped with acoustic modems that provide noisy, range-limited communication. The AUV must plan a path that maximizes the information collected while minimizing travel time or fuel expenditure. We propose AUV path planning methods that extend algorithms for variants of the Traveling Salesperson Problem (TSP). While executing a path, the AUV can improve performance by communicating with multiple nodes in the network at once. Such multi-node communication requires a scheduling protocol that is robust to channel variations and interference. To this end, we examine two multiple access protocols for the underwater data collection scenario, one based on deterministic access and another based on random access. We compare the proposed algorithms to baseline strategies through simulated experiments that utilize models derived from experimental test data. Our results demonstrate that properly designed communication models and scheduling protocols are essential for choosing the appropriate path planning algorithms for data collection.

Abstract — The Arctic seafloor remains one of the last unexplored areas on Earth. Exploration of this unique environment using standard remotely operated oceanographic tools has been obstructed by the dense Arctic ice cover. In the summer of 2007 the Arctic Gakkel Vents Expedition (AGAVE) was conducted with the express intention of understanding aspects of the marine biology, chemistry and geology associated with hydrothermal venting on the section of the mid-ocean ridge known as the Gakkel Ridge. Unlike previous research expeditions to the Arctic the focus was on high resolution imaging and sampling of the deep seafloor. To accomplish our goals we designed two new Autonomous Underwater Vehicles (AUVs) named Jaguar and Puma, which performed a total of nine dives at depths of up to 4062m. These AUVs were used in combination with a towed vehicle and a conventional CTD (conductivity, temperature and depth) program to characterize the seafloor. This paper describes the design decisions and operational changes required to ensure useful service, and facilitate deployment, operation, and recovery in the unique Arctic environment. I.

Simulated annealing is a provably convergent optimizer for single-objective problems. Previously proposed multiobjective extensions have mostly taken the form of a single-objective simulated annealer optimizing a composite function of the objectives. We propose a multiobjective simulated annealer utilizing the relative dominance of a solution as the system energy for optimization, eliminating problems associated with composite objective functions. We also propose a method for choosing perturbation scalings promoting search both towards and across the Pareto front. We illustrate the simulated annealer's performance on a suite of standard test problems and provide comparisons with another multiobjective simulated annealer and the NSGA-II genetic algorithm. The new simulated annealer is shown to promote rapid convergence to the true Pareto front with a good coverage of solutions across it comparing favorably with the other algorithms. An application of the simulated annealer to an industrial problem, the optimization of a code-division-multiple access (CDMA) mobile telecommunications network's air interface, is presented and the simulated annealer is shown to generate nondominated solutions with an even and dense coverage that outperforms single objective genetic algorithm optimizers.

We present a low-cost stereo vision implementation suitable for use in autonomous vehicle applications and designed with agricultural applications in mind. This implementation utilizes the Census transform algorithm to calculate depth maps from a stereo pair of automotive-grade CMOS cameras. The final prototype utilizes commodity hardware, including a Xilinx Spartan-3 FPGA, to process 320times240 pixel images at greater than 150 frames per second and deliver them via a USB 2.0 interface.

The likely sensitivity of an IEEE 802.16e system to optimization of sub-channel preamble power, antenna down-tilt, azimuth and beam-width is evaluated. A simple optimization scheme for these parameters is developed and an initial evaluation is performed. The various criteria by which an 802.16e system may be evaluated are identified and defined. These include signal-to-interference plus noise ratio, blocking and down link data rate and outage. A static model of the air interface is developed to predict these quantities. This model is simplified for reduced computation times, thus enabling a searcher-based optimization. The optimizer is a single-objective greedy local search scheme, driven by the air interface model and including intelligent hot-spot identification. This optimizer is employed to adjust various subsets of the sub-channel preamble power and antenna orientation parameters of the base stations in a simulated system based on a real cellular network. The performance improvements in the chosen criteria predicted by the simplified model are compared for the different scenarios. The predicted average down link rate is seen to increase by more than 50% when all degrees of freedom are exploited. Optimization of antenna parameters is predicted to be significantly more effective than preamble power optimization for enhancing predicted system performance.

Design-for-test techniques for wafer test, component test and system-level diagnostics are implemented on standalone SRAMs at 1 Gb/s/pin. These design-for-test techniques achieve several objectives: improved tester measurement accuracy, higher component yield, and optimal system-level SRAM performance.