3 resultados para Police patrol.

em Universidad Politécnica de Madrid


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A study on the manoeuvrability of a riverine support patrol vessel is made to derive a mathematical model and simulate maneuvers with this ship. The vessel is mainly characterized by both its wide-beam and the unconventional propulsion system, that is, a pump-jet type azimuthal propulsion. By processing experimental data and the ship characteristics with diverse formulae to find the proper hydrodynamic coefficients and propulsion forces, a system of three differential equations is completed and tuned to carry out simulations of the turning test. The simulation is able to accept variable speed, jet angle and water depth as input parameters and its output consists of time series of the state variables and a plot of the simulated path and heading of the ship during the maneuver. Thanks to the data of full-scale trials previously performed with the studied vessel, a process of validation was made, which shows a good fit between simulated and full-scale experimental results, especially on the turning diameter

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Methodology and results of full scale maneuvering trials for Riverine Support Patrol Vessel “RSPV”, built by COTECMAR for the Colombian Navy are presented. !is ship is equipped with a “Pump – Jet” propulsion system and the hull corresponds to a wide-hull with a high Beam – Draft ratio (B/T=9.5). Tests were based on the results of simulation of turning diameters obtained from TRIBON M3© design software, applying techniques of Design of Experiments “DOE”, to rationalize the number of runs in di"erent conditions of water depth, ship speed, and rudder angle. Results validate the excellent performance of this class of ship and show that turning diameter and other maneuvering characteristics improve with decreasing water depth.

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This paper describes the language identification (LID) system developed by the Patrol team for the first phase of the DARPA RATS (Robust Automatic Transcription of Speech) program, which seeks to advance state of the art detection capabilities on audio from highly degraded communication channels. We show that techniques originally developed for LID on telephone speech (e.g., for the NIST language recognition evaluations) remain effective on the noisy RATS data, provided that careful consideration is applied when designing the training and development sets. In addition, we show significant improvements from the use of Wiener filtering, neural network based and language dependent i-vector modeling, and fusion.