Dirani M.,Altran GmbH |
Altman Z.,Orange S.A.
Computer Networks | Year: 2011
Self-organizing networks (SONs) are considered as a driving technology that aims at enhancing usage of radio resources, at simplifying network management, and at reducing cost of operation of next generation radio access networks. This paper describes a framework for designing SON mechanisms for dynamically optimizing Radio Resource Management (RRM) functions. The base station is modeled as an agent that learns from its own local information and that of its neighbors to dynamically optimize RRM parameters. An application of the design framework to SON enabled fractional power control (FPC) in a LTE network is presented. The FPC is particularly important in OFDMA technology as a means to mitigate interference originated by uplink transmission power between neighboring cells. The agent uses fuzzy-reinforcement learning to dynamically adjust the FPC parameter to reach optimal tradeoffs between cell-edge and neighboring cell performance. The learning process is adapted to operate in a sporadic context related to the rapid variations in power, in users' position and in the number of interferers. Results show important gain brought about by the self-optimizing FPC to the network capacity and to the perceived quality for data applications. © 2010 Elsevier B.V. All rights reserved. Source
Ollitrault M.,French National Center for Scientific Research |
Rannou J.-P.,Altran GmbH
Journal of Atmospheric and Oceanic Technology | Year: 2013
During the first decade of the twenty-first century, more than 6000 Argo floats have been launched over the World Ocean, gathering temperature and salinity data from the upper 2000 m, at a 10-day or so sampling period. Meanwhile their deep displacements can be used to map the ocean circulation at their drifting depth (mostly around 1000 m). A comprehensive processing of the whole Argo dataset collected prior to 1 January 2010 has been performed to produce a world-wide dataset of deep displacements. This numerical atlas, named ANDRO, after a traditional dance of Brittany meaning a swirl, comprises some 600 000 deep displacements. These displacements, based on Argo or GPS surface locations only, havebeen fully checked and corrected for possible errors found in the public Argo data files (due to incorrect decoding or instrumental failure). Park pressures measured by the floats while drifting at depth are preserved in ANDRO (less than 2% of the park pressures are unknown): 63% of the float displacements are in the layer (900, 1100) dbar with a good (more or less uniform) degree of coverage of all the oceans, except around Antarctica (south of 608S). Two deeper layers-(1400, 1600) and (1900, 2100) dbar-are also sampled (11% and 8% of the float displacements, respectively) but with poorer geographical coverage. Grounded cycles (i.e., if the float hits the sea bottom) are excluded. ANDRO is available online as an ASCII file. © 2013 American Meteorological Society. Source
Arrospide J.,Technical University of Madrid |
Arrospide J.,Altran GmbH |
Salgado L.,Technical University of Madrid |
Salgado L.,Autonomous University of Madrid
IEEE Transactions on Image Processing | Year: 2013
Vehicle detection based on image analysis has attracted increasing attention in recent years due to its low cost, flexibility, and potential toward collision avoidance. In particular, vehicle verification is especially challenging on account of the heterogeneity of vehicles in color, size, pose, etc. Image-based vehicle verification is usually addressed as a supervised classification problem. Specifically, descriptors using Gabor filters have been reported to show good performance in this task. However, Gabor functions have a number of drawbacks relating to their frequency response. The main contribution of this paper is the proposal and evaluation of a new descriptor based on the alternative family of log-Gabor functions for vehicle verification, as opposed to existing Gabor filter-based descriptors. These filters are theoretically superior to Gabor filters as they can better represent the frequency properties of natural images. As a second contribution, and in contrast to existing approaches, which transfer the standard configuration of filters used for other applications to the vehicle classification task, an in-depth analysis of the required filter configuration by both Gabor and log-Gabor descriptors for this particular application is performed for fair comparison. The extensive experiments conducted in this paper confirm that the proposed log-Gabor descriptor significantly outperforms the standard Gabor filter for image-based vehicle verification. © 1992-2012 IEEE. Source
Agency: Cordis | Branch: H2020 | Program: CS2-IA | Phase: JTI-CS2-2014-CFP01-FRC-02-04 | Award Amount: 529.81K | Year: 2016
The objective of this topic is to set up an industrial and fully automatic optimal design tool, integrating software identified by the Topic Leader, in order to reach TRL6 at the end of the project. This tool has to be dedicated to rotorcraft engine air intake analysis and able to handle multi-objective, multi-parameters and multi-points optimization on a given CATIA CAD. An effective aerodynamic design of the engine air intakes is essential for ensuring a proper air supply to the first stage compressor and thus an efficient behavior of the whole engine installation. However, its optimization has to deal with a lot of requirements and constraints, not always linked to the engine performance itself, but often aiming at improving conflicting criterions. For instance, the engine air intakes design will have some impact as regards the three following different issues: Volume specifications Helicopter manufacturer specifications, along with the airframe performance level required Engine manufacturer specifications, along with the engine performance level required In order to achieve the task, optimization will take into account 3 flight conditions. Among all optimization strategy available, due to CFD solver limited capabilities for adjoint computations, a Surrogate Based Optimization approach is proposed. It allows use of gradient free and global optimization method. Two optimizations are planned during the task: one without Inlet Barrier Filter and a last without. The final objective is to improve flow solution at Air Intake Plane from a distorsion and pressure losses aspect.
Altran GmbH | Date: 2012-03-23
Methods and apparatuses relate to repairing a conduit having a defect and providing the conduit with structural support. A support member may be positioned along the inner surface of a conduit covering a defect. A sealing member may be disposed along a periphery of the support member so as to provide an obstruction to fluid flow between an outer surface of the support member and the inner surface of the conduit. One or more retaining members may apply a suitable pressure to the sealing member and support member to maintain obstruction to fluid flow between the interior and the exterior of the conduit. The support member may provide the repaired conduit with a greater degree of structural integrity and strength at the site of the defect than would otherwise be available.