Graffiti Networks: A Subversive, Internet-Scale File Sharing Model

The proliferation of peer-to-peer (P2P) file sharing protocols is due to their efficient and scalable methods for data dissemination to numerous users. But many of these networks have no provisions to provide users with long term access to files after the initial interest has diminished, nor are they able to guarantee protection for users from malicious clients that wish to implicate them in incriminating activities. As such, users may turn to supplementary measures for storing and transferring data in P2P systems. We present a new file sharing paradigm, called a Graffiti Network, which allows peers to harness the potentially unlimited storage of the Internet as a third-party intermediary. Our key contributions in this paper are (1) an overview of a distributed system based on this new threat model and (2) a measurement of its viability through a one-year deployment study using a popular web-publishing platform. The results of this experiment motivate a discussion about the challenges of mitigating this type of file sharing in a hostile network environment and how web site operators can protect their resources

Using Thermochromic Materials for Mobile Space Suit Heating Applications

In past research we investigated and proposed the use of an intermediate environment [2]. It is termed an intermediate environment because it has the pressure of the living quarters but uses plentiful Martian air as the ambient. The use of an intermediate environment can solve the pressure requirement effectively. An intermediate environment pressurized with Martian air would provide sufficient external pressure, allowing the use of a thinner, light-weight suit. The astronauts would need oxygen or mixed gas masks, but would not need their bulky outside suits to provide counter pressure. This will allow improved mobility, dexterity, visibility and astronaut energy efficiency. An intermediate environment also has additional benefits in minimizing flammability concerns, minimizing decompression sickness, and saving cost on resources

Automating Steady and Unsteady Adjoints: Efficiently Utilizing Implicit and Algorithmic Differentiation

Algorithmic differentiation (AD) has become increasingly capable and straightforward to use. However, AD is inefficient when applied directly to solvers, a feature of most engineering analyses. We can leverage implicit differentiation to define a general AD rule, making adjoints automatic. Furthermore, we can leverage the structure of differential equations to automate unsteady adjoints in a memory efficient way. We also derive a technique to speed up explicit differential equation solvers, which have no iterative solver to exploit. All of these techniques are demonstrated on problems of various sizes, showing order of magnitude speed-ups with minimal code changes. Thus, we can enable users to easily compute accurate derivatives across complex analyses with internal solvers, or in other words, automate adjoints using a combination of AD and implicit differentiation.Comment: 12 pages, 3 figure

Gradient-Based Optimization of Solar-Regenerative High-Altitude Long-Endurance Aircraft

In this paper we use gradient-based optimization to minimize the mass of a solar-regenerative high-altitude long-endurance (SR-HALE) flying-wing aircraft while accounting for nonlinear aeroelastic effects. We design the aircraft to fly year round at 35° latitude at 18km above sea level and subject the aircraft to energy capture, energy storage, material failure, local buckling, stall, longitudinal stability, and coupled flight and aeroelastic stability constraints. The optimized aircraft has an aspect ratio of 27:8, a surface area of 99:1m2, and a mass of 508:8 kg. Our results suggest that thick airfoils provide greater structural efficiency than increased carbon fiber reinforced polymer (CFRP) ply thicknesses. We also perform several parameter sweeps to determine sensitivity to altitude, latitude, battery specific energy, solar efficiency, avionics and payload power requirements, and minimum design velocity

Grey swan tropical cyclones

We define ‘grey swan’ tropical cyclones as high-impact storms that would not be predicted based on history but may be foreseeable using physical knowledge together with historical data. Here we apply a climatological–hydrodynamic method to estimate grey swan tropical cyclone storm surge threat for three highly vulnerable coastal regions. We identify a potentially large risk in the Persian Gulf, where tropical cyclones have never been recorded, and larger-than-expected threats in Cairns, Australia, and Tampa, Florida. Grey swan tropical cyclones striking Tampa, Cairns and Dubai can generate storm surges of about 6 m, 5.7 m and 4 m, respectively, with estimated annual exceedance probabilities of about 1/10,000. With climate change, these probabilities can increase significantly over the twenty-first century (to 1/3,100–1/1,100 in the middle and 1/2,500–1/700 towards the end of the century for Tampa). Worse grey swan tropical cyclones, inducing surges exceeding 11 m in Tampa and 7 m in Dubai, are also revealed with non-negligible probabilities, especially towards the end of the century

Learning and Adaptation in a Recurrent Model of V1 Orientation Selectivity

Learning and adaptation in the domain of orientation processing are among the most studied topics in the literature. However, little effort has been devoted to explaining the diverse array of experimental findings via a physiologically based model. We have started to address this issue in the framework of the recurrent model of V1 orientation selectivity and found that reported changes in V1 orientation tuning curves after learning and adaptation can both be explained with the model. Specifically, the sharpening of orientation tuning curves near the trained orientation after learning can be accounted for by slightly reducing net excitatory connections to cells around the trained orientation, while the broadening and peak shift of the tuning curves after adaptation can be reproduced by appropriately scaling down both excitation and inhibition around the adapted orientation. In addition, we investigated the perceptual consequences of the tuning curve changes induced by learning and adaptation using signal detection theory. We found that in the case of learning, the physiological changes can account for the psychophysical data well. In the case of adaptation, however, there is a clear discrepancy between the psychophysical data from alert human subjects and the physiological data from anesthetized animals. Instead, human adaptation studies can be better accounted for by the learning data from behaving animals. Our work suggests that adaptation in behaving subjects may be viewed as a short-term form of learning

V1 orientation plasticity is explained by broadly tuned feedforward inputs and intracortical sharpening

Orientation adaptation and perceptual learning change orientation tuning curves of V1 cells. Adaptation shifts tuning curve peaks away from the adapted orientation, reduces tuning curve slopes near the adapted orientation, and increases the responses on the far flank of tuning curves. Learning an orientation discrimination task increases tuning curve slopes near the trained orientation. These changes have been explained previously in a recurrent model (RM) of orientation selectivity. However, the RM generates only complex cells when they are well tuned, so that there is currently no model of orientation plasticity for simple cells. In addition, some feedforward models, such as the modified feedforward model (MFM), also contain recurrent cortical excitation, and it is unknown whether they can explain plasticity. Here, we compare plasticity in the MFM, which simulates simple cells, and a recent modification of the RM (MRM), which displays a continuum of simple-to-complex characteristics. Both pre- and postsynaptic-based modifications of the recurrent and feedforward connections in the models are investigated. The MRM can account for all the learning- and adaptation-induced plasticity, for both simple and complex cells, while the MFM cannot. The key features from the MRM required for explaining plasticity are broadly tuned feedforward inputs and sharpening by a Mexican hat intracortical interaction profile. The mere presence of recurrent cortical interactions in feedforward models like the MFM is insufficient; such models have more rigid tuning curves. We predict that the plastic properties must be absent for cells whose orientation tuning arises from a feedforward mechanism

Inviscid Analysis of Extended Formation Flight

Flying airplanes in extended formations, with separation distances of tens of wingspans, significantly improves safety while maintaining most of the fuel savings achieved in close formations. The present study investigates the impact of roll trim and compressibility at fixed lift coefficient on the benefits of extended formation flight. An Euler solver with adjoint-based mesh refinement combined with a wake propagation model is used to analyze a two-body echelon formation at a separation distance of 30 spans. Two geometries are examined: a simple wing and a wing-body geometry. Energy savings, quantified by both formation drag fraction and span efficiency factor, are investigated at subsonic and transonic speeds for a matrix of vortex locations. The results show that at fixed lift and trimmed for roll, the optimal location of vortex impingement is about 10% inboard of the trailing airplane s wing-tip. Interestingly, early results show the variation in drag fraction reduction is small in the neighborhood of the optimal position. Over 90% of energy benefits can be obtained with a 5% variation in transverse and 10% variation in crossflow directions. Early results suggest control surface deflections required to achieve trim reduce the benefits of formation flight by 3-5% at subsonic speeds. The final paper will include transonic effects and trim on extended formation flight drag benefits