44,050 research outputs found

    Radiation environment for rendezvous and docking with nuclear rockets

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    Radiation environment data for the NERVA engine are provided which may be utilized in estimating radiation exposures associated with various space maneuvers. Spatial distributions of neutron and gamma tissue kerma rates produced during full thrust operation of the engine are presented. Final rendezvous with an orbiting space station would be achieved subsequent to full thrust operation during a period of 10 or more hours duration in which impulse is delivered by the propellant used for removal of decay heat. Consequently, post operation radiation levels are of prime importance in estimating space station exposures. Maps of gamma kerma rates around the engine are provided for decay times of 4 and 24 hours after a representative firing. Typical decay curves illustrating the dependence of post operation kerma rates on decay time and operating history are included. Examples of the kerma distributions around the engine which result from integration over specific exposure periods are shown

    Consensus Acceleration in Multiagent Systems with the Chebyshev Semi-Iterative Method

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    We consider the fundamental problem of reaching consensus in multiagent systems; an operation required in many applications such as, among others, vehicle formation and coordination, shape formation in modular robotics, distributed target tracking, and environmental modeling. To date, the consensus problem (the problem where agents have to agree on their reported values) has been typically solved with iterative decentralized algorithms based on graph Laplacians. However, the convergence of these existing consensus algorithms is often too slow for many important multiagent applications, and thus they are increasingly being combined with acceleration methods. Unfortunately, state-of-the-art acceleration techniques require parameters that can be optimally selected only if complete information about the network topology is available, which is rarely the case in practice. We address this limitation by deriving two novel acceleration methods that can deliver good performance even if little information about the network is available. The first proposed algorithm is based on the Chebyshev semi-iterative method and is optimal in a well defined sense; it maximizes the worst-case convergence speed (in the mean sense) given that only rough bounds on the extremal eigenvalues of the network matrix are available. It can be applied to systems where agents use unreliable communication links, and its computational complexity is similar to those of simple Laplacian-based methods. This algorithm requires synchronization among agents, so we also propose an asynchronous version that approximates the output of the synchronous algorithm. Mathematical analysis and numerical simulations show that the convergence speed of the proposed acceleration methods decrease gracefully in scenarios where the sole use of Laplacian-based methods is known to be impractical

    Determine utility of ERTS-1 to detect and monitor area strip mining and reclamation

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    The author has identified the following significant results. Computer techniques were applied to process ERTS tapes acquired over coal mining operations in southeastern Ohio on 21 August 1972 and 3 September 1973. ERTS products obtained included geometrically correct map overlays showing stripped earth, partially reclaimed earth, water, and natural vegetation. Computer-generated tables listing the area covered by each land-water category in square kilometers and acres were produced. By comparing these mapping products, the study demonstrates the capability of ERTS to monitor changes in the extent of stripping, success of reclamation, and the secondary effects of mining on the environment

    Numerical Algorithm for Detecting Ion Diffusion Regions in the Geomagnetic Tail with Applications to MMS Tail Season May 1 -- September 30, 2017

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    We present a numerical algorithm aimed at identifying ion diffusion regions (IDRs) in the geomagnetic tail, and test its applicability. We use 5 criteria applied in three stages. (i) Correlated reversals (within 90 s) of Vx and Bz (at least 2 nT about zero; GSM coordinates); (ii) Detection of Hall electric and magnetic field signatures; and (iii) strong (>10 mV/m) electric fields. While no criterion alone is necessary and sufficient, the approach does provide a robust, if conservative, list of IDRs. We use data from the Magnetospheric Multiscale Mission (MMS) spacecraft during a 5-month period (May 1 to September 30, 2017) of near-tail orbits during the declining phase of the solar cycle. We find 148 events satisfying step 1, 37 satisfying steps 1 and 2, and 17 satisfying all three, of which 12 are confirmed as IDRs. All IDRs were within the X-range [-24, -15] RE mainly on the dusk sector and the majority occurred during traversals of a tailward-moving X-line. 11 of 12 IDRs were on the dusk-side despite approximately equal residence time in both the pre- and post-midnight sectors (56.5% dusk vs 43.5% dawn). MMS could identify signatures of 4 quadrants of the Hall B-structure in 3 events and 3 quadrants in 7 of the remaining 12 confirmed IDRs identified. The events we report commonly display Vx reversals greater than 400 km/s in magnitude, normal magnetic field reversals often >10 nT in magnitude, maximum DC |E| which are often well in excess of the threshold for stage 3. Our results are then compared with the set of IDRs identified by visual examination from Cluster in the years 2000-2005.Comment: In Submission at JGR:Space Physic

    Breaking the habit: measuring and predicting departures from routine in individual human mobility

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    Researchers studying daily life mobility patterns have recently shown that humans are typically highly predictable in their movements. However, no existing work has examined the boundaries of this predictability, where human behaviour transitions temporarily from routine patterns to highly unpredictable states. To address this shortcoming, we tackle two interrelated challenges. First, we develop a novel information-theoretic metric, called instantaneous entropy, to analyse an individual’s mobility patterns and identify temporary departures from routine. Second, to predict such departures in the future, we propose the first Bayesian framework that explicitly models breaks from routine, showing that it outperforms current state-of-the-art predictor

    A Feynman-Kac Formula for Anticommuting Brownian Motion

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    Motivated by application to quantum physics, anticommuting analogues of Wiener measure and Brownian motion are constructed. The corresponding Ito integrals are defined and the existence and uniqueness of solutions to a class of stochastic differential equations is established. This machinery is used to provide a Feynman-Kac formula for a class of Hamiltonians. Several specific examples are considered.Comment: 21 page

    The M Series Absorption Spectra of Osmium Iridium and Platinum

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    Spectrograms have been obtained of all but three of the predicted M series absorption limits of osmium, iridium, and platinum. A vacuum spectrograph of the Siegbahn type was used in this work. The slit of the spectrometer chamber was covered with a very thin celluloid film, smoked over a kerosene flame until sufficiently darkened to keep out the light of the incandescent filament. To make the film, celluloid was dissolved in amyl acetate and thinned until about like molasses. One small drop on the surface of water spread out forming a film two or three inches in diameter. After the amyl acetate had dissolved the film was lifted on a circular wire frame. After being dried, it was mounted over the slit with cement

    Asking the experts : developing and validating parental diaries to assess children's minor injuries

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    The methodological issues involved in parental reporting of events in children's everyday lives are discussed with reference to the development and validation of an incident diary, collecting concurrent data on minor injuries in a community study of children under eight years old. Eighty-two mothers participated in a comparison over nine days of daily telephone interviews and structured incident diaries. Telephone methods resulted in more missing data, and participants in both groups expressed a preference for the diary method. This diary was then validated on a sample of 56 preschool and school-aged children by comparing injury recording by a research health visitor with that of their mothers. Each failed to report some injuries, but there was good agreement overall, and in descriptive data on injuries reported by both. Parental diaries have the potential to provide rich data, of acceptable validity, on minor events in everyday life

    Sequential Decision Making with Untrustworthy Service Providers

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    In this paper, we deal with the sequential decision making problem of agents operating in computational economies, where there is uncertainty regarding the trustworthiness of service providers populating the environment. Specifically, we propose a generic Bayesian trust model, and formulate the optimal Bayesian solution to the exploration-exploitation problem facing the agents when repeatedly interacting with others in such environments. We then present a computationally tractable Bayesian reinforcement learning algorithm to approximate that solution by taking into account the expected value of perfect information of an agent's actions. Our algorithm is shown to dramatically outperform all previous finalists of the international Agent Reputation and Trust (ART) competition, including the winner from both years the competition has been run
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