Small unmanned airborne systems to support oil and gas pipeline monitoring and mapping

Acknowledgments We thank Johan Havelaar, Aeryon Labs Inc., AeronVironment Inc. and Aeronautics Inc. for kindly permitting the use of materials in Fig. 1.Peer reviewedPublisher PD

Earth and Wind Industries Playing with Fire: The Concurrent Rights of Wind Farm Operators, Oil and Gas Developers, and Landowners in Kansas

This is the published version

Dimensional Duality

We show that string theory on a compact negatively curved manifold, preserving a U(1)^{b_1} winding symmetry, grows at least b_1 new effective dimensions as the space shrinks. The winding currents yield a "D-dual" description of a Riemann surface of genus h in terms of its 2h dimensional Jacobian torus, perturbed by a closed string tachyon arising as a potential energy term in the worldsheet sigma model. D-branes on such negatively curved manifolds also reveal this structure, with a classical moduli space consisting of a b_1-torus. In particular, we present an AdS/CFT system which offers a non-perturbative formulation of such supercritical backgrounds. Finally, we discuss generalizations of this new string duality.Comment: 25 pages, harvmac. v2: fixed typo. v3: fixed typos and added ref

User's guide to programming fault injection and data acquisition in the SIFT environment

Described are the features, command language, and functional design of the SIFT (Software Implemented Fault Tolerance) fault injection and data acquisition interface software. The document is also intended to assist and guide the SIFT user in defining, developing, and executing SIFT fault injection experiments and the subsequent collection and reduction of that fault injection data. It is also intended to be used in conjunction with the SIFT User's Guide (NASA Technical Memorandum 86289) for reference to SIFT system commands, procedures and functions, and overall guidance in SIFT system programming

Cluster, Classify, Regress: A General Method For Learning Discountinous Functions

This paper presents a method for solving the supervised learning problem in which the output is highly nonlinear and discontinuous. It is proposed to solve this problem in three stages: (i) cluster the pairs of input-output data points, resulting in a label for each point; (ii) classify the data, where the corresponding label is the output; and finally (iii) perform one separate regression for each class, where the training data corresponds to the subset of the original input-output pairs which have that label according to the classifier. It has not yet been proposed to combine these 3 fundamental building blocks of machine learning in this simple and powerful fashion. This can be viewed as a form of deep learning, where any of the intermediate layers can itself be deep. The utility and robustness of the methodology is illustrated on some toy problems, including one example problem arising from simulation of plasma fusion in a tokamak.Comment: 12 files,6 figure

Radiative instabilities in simulations of spherically symmetric supernova blast waves

High-resolution simulations of the cooling regions of spherically symmetric supernova remnants demonstrate a strong radiative instability. This instability, whose presence is dependent on the shock velocity, causes large-amplitude fluctuations in the shock velocity. The fluctuations begin almost immediately after the radiative phase begins (upon shell formation) if the shock velocity lies in the unstable range; they last until the shock slows to speeds less than approximately 130 km/s. We find that shock-velocity fluctuations from the reverberations of waves within the remnant are small compared to those due to the instability. Further, we find (in plane-parallel simulations) that advected inhomogeneities from the external medium do not interfere with the qualitative nature of the instability-driven fluctuations. Large-amplitude inhomogeneities may alter the phases of shock-velocity fluctuations, but do not substantially reduce their amplitudes.Comment: 18 pages text, LaTeX/AASTeX (aaspp4); 10 figures; accepted by Ap

The Relationship between Cost Analysis and Program Management

Cost analysis if often viewed as applying basic principles and cost methodologies to determine total system cost. These finished estimates then flow into a decision making process and the cost estimator leaves the stage. Reality shows that the cost estimator is actually one of the main contributors to the decision making process. Our introduction to this special issue explores the areas where cost estimating plays a major role in program management in areas beyond the normal program estimate. We have included articles that show the key role estimators can play in source selection strategies and evaluation; cost of delay analysis for management decisions, earned value management methods to predict program costs; decision criteria to rank competing projects that complement traditional cost-based methods; and a new methodology for determining research and development budget profiles

The Potential of Drone Technology in Pandemics

Publisher PD