archive-fr.com » FR » O » OPUS-PROJECT.FR

Total: 702

Choose link from "Titles, links and description words view":

Or switch to "Titles and links view".
  • UJF (Université Joseph Fourier), Laboratoire Jean Kuntzmann (LJK)
    of the UJF the INPG the UPMF the CNRS and INRIA it combines the forces of applied mathematicians and statisticians from the former laboratories LMC and LabSAD with graphics and computer vision experts from the former laboratory GRAVIR Its expertise centres on the computational and statistical sciences and their uses in analysing natural phenomena with applications ranging from environmental modelling through life sciences nanosciences visualisation and signal processing to mathematical finance The laboratory is structured into three scientific departments Geometry Images focuses on geometric modelling and image processing including graphics and computer vision Deterministic Models Algorithms develops tools for numerical and symbolic computation Statistics gathers theoretical and applied statisticians and specialists in data analysis and signal processing Joseph Fourier University is be represented by two of its professors Anestis Antoniadis et Christophe Prud homme who contribute in three areas to the OPUS project i the creation organisation and management of the college of experts that overlooks the scientific developments of the project and provide advices ii propose and implement efficient standard and new methods for the prediction of complex systems based on statistical approaches and iii propose and implement fast and reliable predictions for partial differential equations Joseph Fourier University

    Original URL path: http://www.opus-project.fr/index.php/anropusproject/59-ujf (2016-01-11)
    Open archived version from archive


  • ANR project Opus
    computation infrastructure This branch also develops Web solutions ENGINEERING focuses on the development of new services based on the Statistical and Data Mining methodologies SOFTIA s skillset covers numerous software technologies and is particularly focused on Open Source Softia website Last Updated Monday 11 January 2010 22 38 UP7 Université Paris VII laboratoire Probabilités et Modèles Aléatoires LPMA Monday 21 December 2009 21 34 Author Administrator LPMA is is a joint laboratory of the Universités Paris VI and Paris VII It comprises about 70 faculties and 50 PhD students The laboratory s activities take place in the applied mathematics field and focuses on modelisation description and analysis of random phenomena Uncertainty quantification in numerical codes has become one of the main research axes from the joint action of strong demand from academic and industrial partners as well as recent developments using advanced techniques from both numerical simulation and probabilistic tools point of view variance reduction methods for Monte Carlo genetic algorithms interacting particle systems LPMA hosts the activities of two Master s 2 Degrees which represent more than 200 students each year a great pool which allows about 50 PhD students at any time The scientific person in charge of OPUS project also participates in those two Master s degrees He was the main organizer of CEMRACS 2006 This mathematical summer center for advanced research in scientific computing was dedicated to modeling randomness and uncertainty propagation smai emath fr cemracs cemracs06 Partners within OPUS such as CEA EADS and EDF have strongly involved themselves in CEMRACS by offering several research projects which were short six weeks but intense They were completed throughout the summer and led to the writing of internal reports and publications in the following months The fruitful collaborations started during CEMRACS should be supported by a new stimulus which the OPUS project could be head of UP7 website Last Updated Tuesday 26 January 2010 21 11 UJF Université Joseph Fourier Laboratoire Jean Kuntzmann LJK Monday 21 December 2009 21 33 Author Administrator The Jean Kuntzmann laboratory is an Applied Mathematics and Computer Science laboratory created in January 2007 in Grenoble France A joint research unit of the UJF the INPG the UPMF the CNRS and INRIA it combines the forces of applied mathematicians and statisticians from the former laboratories LMC and LabSAD with graphics and computer vision experts from the former laboratory GRAVIR Its expertise centres on the computational and statistical sciences and their uses in analysing natural phenomena with applications ranging from environmental modelling through life sciences nanosciences visualisation and signal processing to mathematical finance The laboratory is structured into three scientific departments Geometry Images focuses on geometric modelling and image processing including graphics and computer vision Deterministic Models Algorithms develops tools for numerical and symbolic computation Statistics gathers theoretical and applied statisticians and specialists in data analysis and signal processing Joseph Fourier University is be represented by two of its professors Anestis Antoniadis et Christophe Prud homme who contribute in three areas to the OPUS

    Original URL path: http://www.opus-project.fr/index.php/anropusproject?start=5 (2016-01-11)
    Open archived version from archive

  • ANR project Opus
    Information systems engineering Within axis 1 we especially study numerical techniques applied to PDEs for multiphasic problems or materials as well as optimization methods The lab is 60 people strong and is associated to two teaching structures from Ecole Centrale Paris Applied Mathematics and IT Telecom options mostly within research initiation projects It is also a partner for several Masters Degrees INSTN Paris V Université Dauphine Sorbonne Université Evry and has two strategic partnerships with CEA and INRIA On the uncertainties in multidisciplinary conception theme the lab is involved in projects OMD Optimisation Multi Disciplinaire from ANR as well as IOLS and EHPOC from the SYSTEM TIC PARIS REGION competitivity pole ECP website EDF Electricité de France Recherche et Développement R D Monday 21 December 2009 03 25 Author Administrator The EDF Group is a leading player in the European energy industry active in all areas of the electricity value chain from generation to trading and increasingly active in the gas chain in Europe Leader in the French electricity market the Group also has solid positions in the United Kingdom Germany and Italy The mission of EDF R D is to contribute to improving performance among EDF Group operating units and to identify and prepare new growth drivers for the medium and long terms EDF R D has a committed policy of working with partners in France and Europe especially the countries where the Group is active as well as in other parts of the world Uncertainty assessment and propagation in physical environmental or risk modeling is the subject of a long standing work at EDF R D Thanks to a multitude of application fields for these techniques and methods EDF has acquired a consolidated know how in generic approaches to these problems and has contributed to the definition to a generic Guide to quantitative uncertainty management shared with many industrial and academic partners EDF R D is involved in many partnership and projects about uncertainty and develops together with EADS and Phimeca the Open TURNS software EDF website EDF R D website Open TURNS Last Updated Tuesday 23 February 2010 21 43 EADS European Aeronautic Defence and Space company Innovation Works Monday 21 December 2009 02 47 Author Administrator EADS Innovation Works develops tools and skills for usage by the various entities of the EADS group Airbus Ariane Eurocopter MBDA Astrium The Simulation Systems and IT for Applied Mathematics department develops methods and computing tools from applied mathematics techniques and scientific computation Numerical Analysis Applied Probabilities Parallel computing Grid Computing In the last few years uncertainty management is at the heart of EADS IW computing strategy Indeed for needs of advanced conception as well as numerical certification intensive use of numerical computation tools requires the identification and development of trust indicators Indeed mastery of stochastic computing techniques and data management is mandatory EADS IW is involved in projects IOLS and EHPOC from SYSTEM TIC PARIS REGION pole as well as developing tools and methods around uncertainty management OpenTURNS platform

    Original URL path: http://www.opus-project.fr/index.php/anropusproject?start=10 (2016-01-11)
    Open archived version from archive

  • ANR project Opus
    for Generic Uncertainty Treatment Since many years industry regulators require an uncertainty statement to be provided with any modelling study in industrial risk assessment field Other stakeholders at different levels follow as far as system design or risk assessment is concerned Indeed an overall awareness of uncertainties and a need to take it account when deciding into is spreading fast While many approaches typically specific and problem driven had been imagined and developed since late 90ies by various industries ranging from Defence to Medical to Energy ever widening spectrum of possible applications yielded a know how consolidation economically sensible A number of academic references have been published in the 1990s originating from the risk assessment community firstly in the United States where major uncertainty research has been launched in the energy or military aerospace industries Helton Oberkampf etc and later on in Europe Aven as well as from the environmental or infrastructure impact and planning Granger Mc Henrion Saltelli Cooke Meanwhile some physical domains have enjoyed sectoral modelling research such as probabilistic mechanics e g Melchers involving most recently stochastic developments It is only gradually that the scientific computing communities and the larger industrial computing actors have started to get seriously involved in the advanced applied mathematics and high performance computing consequences and opportunities attached to uncertainty modelling Most historical works published in the 1990s involved some simple simulators with only rarely full scale finite element or advanced coupled models or physically limited modelling efforts such as mechanics not recognising the genericity that did appear only later on Hence nowadays several major partnerships at the international level ESREDA MUCM SAMSI or the French level IMdR have launched ambitious works to capitalise on uncertainty treatments into generic guides that would meet virtually any industrial need It aims at designing a common template to be followed as well as specific guidelines to methodology that might best fit the particular case typically according to the data and experts information availability model complexity and so on The genuine study cases considered in these projects all from different business areas illustrate a startling feature although the applications and physics involved are completely different the implicit mathematical structure seems very similar Moreover the methodology collections to shop in for each step are common and the choice is rather dependent on the criteria the underlying institutional regulation or study purpose than on the application Indeed the conceptual framework that fits conceptually at least virtually any industrial uncertainty study can be resumed by the following figure This scheme ought to be considered as a skeleton for a purely uncertainty part of an industrial study So far all the three essential steps as well as satellites B and C may be shown application free it is rather mutually dependent At a conceptual level it may be one size fits all solution meanwhile it is not assumed to be so when applied Instead the reference guide provides the methodologies to shop from and the guidelines to chose from that handleads

    Original URL path: http://www.opus-project.fr/index.php/anropusproject?start=15 (2016-01-11)
    Open archived version from archive

  • ANR project Opus
    MUCM SAMSI IMdR have launched ambitious works to capitalise on uncertainty treatments into generic guides that would meet virtually any industrial need It aims at designing a common template to be followed as well as specific guidelines to methodology that might best fit the particular case typically according to the data and experts information availability model complexity and so on In order to reach a broad stakeholder community ranging from physicists to company managers with uncertainty awareness and management capacity an essential step the OPUS project target is to create a genuinely generic and comprehensive software platform OPUS capitalises on the most advanced conceptual and guidelines work into an Open Source however industrialised and fully serviced software product OPUS has gathered the specialists from all relevant fields Ecole Centrale de Paris ECP SUPELEC industry oriented uncertainty research INRIA Host of Scilab Consortium Among other INRIA projects and major advances Scilab is a renowned French Open Source Software in scientific computing Joseph Fourier University and Paris VII University applied mathematicians with connections to R and Scilab Octave recognised Open Source Software CEA EADS EDF and Dassault Aviation leading players in building an industrial consensus over the Generic Uncertainty Treatment Guidelines for industrial use ESREDA EHPOC SOFTIA French start up company with strong records of providing the large companies with services around Open Source solutions Therefore OPUS project leverages much greater know how and resources than reflected by the project balance sheet The synergy of partner experiences provides OPUS with critical weight to launch a Generic Open Source Uncertainty Treatment Platform and create a sustainable dynamic to ensure its durability OPUS promotes the transparency in the uncertainty treatment approaches it adopts Therefore OPUS platform is kept open to scrutiny and potential critics that lead to upgrade and ensure the progress OPUS contributes to the emerging Open Source community in the Complex System Development as platform respects current standards and ensures the interoperability with existing and emerging High Performance Simulation tools Indeed OPUS partnership ensures the close cooperation with other major Open Source projects in the field of Complex System Development EHPOC SCILAB SCOS TER TEC as it is packed with active players in these projects OPUS objectives in brief The existence in France of a Generic Integrated Uncertainty Treatment Platform for Simulation and Design of Complex Systems That allows for Uncertainty aware modelling with cutting edge tools Sustainable Dynamic in the Uncertainty Treatment Field Maintain the cutting edge French know how in industry oriented uncertainty research That promotes the Open Source Software for High Performance Modelling and Complex System conception That establishes France as a major hub in the international Industrial Open Source Software map Keywords Complex Systems High Performance Simulation Platform Open Source Uncertainty Treatments Further reading Objectives detailed Value generation Last Updated Monday 21 December 2009 01 29 Project goals Sunday 22 November 2009 20 11 Author Administrator The aim of OPUS Open source Platform for Uncertainty treatment in Simulation project is to create and sustain an activity around Generic

    Original URL path: http://www.opus-project.fr/index.php/anropusproject?start=20 (2016-01-11)
    Open archived version from archive

  • ANR project Opus
    become the work environment for the specialist of the treatment of uncertainties Targeted users are once again industrial practitioners those who identify the treatment of uncertainties as a full task which can be spread to multiple engineering domains a python module with high level operators in the probabilistic and statistical field The interest of this language is to be both a powerful scientific language capable of using C libraries and a user friendly interpreted language like Matlab s one This python module was designed to make the development of prototypes easier in order to test new algorithms and methods for example to become an easy to use support for educational works This module intends to become a natural environment capable of integrating new developments within the field of uncertainty and sensitivity analysis The targeted users are here research centres and the academic community Website Last Updated Monday 11 January 2010 22 39 R Monday 04 January 2010 02 48 Author Administrator R R is a language and environment for statistical computing and graphics It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories formerly AT T now Lucent Technologies by John Chambers and colleagues R can be considered as a different implementation of S There are some important differences but much code written for S runs unaltered under R R provides a wide variety of statistical linear and nonlinear modelling classical statistical tests time series analysis classification clustering and graphical techniques and is highly extensible The S language is often the vehicle of choice for research in statistical methodology and R provides an Open Source route to participation in that activity One of R s strengths is the ease with which well designed publication quality plots can be produced including mathematical symbols and formulae where needed Great care has been taken over the defaults for the minor design choices in graphics but the user retains full control R is available as Free Software under the terms of the Free Software Foundation s GNU General Public License in source code form It compiles and runs on a wide variety of UNIX platforms and similar systems including FreeBSD and Linux Windows and MacOS The R environment R is an integrated suite of software facilities for data manipulation calculation and graphical display It includes an effective data handling and storage facility a suite of operators for calculations on arrays in particular matrices a large coherent integrated collection of intermediate tools for data analysis graphical facilities for data analysis and display either on screen or on hardcopy and a well developed simple and effective programming language which includes conditionals loops user defined recursive functions and input and output facilities The term environment is intended to characterize it as a fully planned and coherent system rather than an incremental accretion of very specific and inflexible tools as is frequently the case with other data analysis software R like S is designed around a true computer

    Original URL path: http://www.opus-project.fr/index.php/anropusproject?el_mcal_month=12&el_mcal_year=2015 (2016-01-11)
    Open archived version from archive

  • ANR project Opus
    to become the work environment for the specialist of the treatment of uncertainties Targeted users are once again industrial practitioners those who identify the treatment of uncertainties as a full task which can be spread to multiple engineering domains a python module with high level operators in the probabilistic and statistical field The interest of this language is to be both a powerful scientific language capable of using C libraries and a user friendly interpreted language like Matlab s one This python module was designed to make the development of prototypes easier in order to test new algorithms and methods for example to become an easy to use support for educational works This module intends to become a natural environment capable of integrating new developments within the field of uncertainty and sensitivity analysis The targeted users are here research centres and the academic community Website Last Updated Monday 11 January 2010 22 39 R Monday 04 January 2010 02 48 Author Administrator R R is a language and environment for statistical computing and graphics It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories formerly AT T now Lucent Technologies by John Chambers and colleagues R can be considered as a different implementation of S There are some important differences but much code written for S runs unaltered under R R provides a wide variety of statistical linear and nonlinear modelling classical statistical tests time series analysis classification clustering and graphical techniques and is highly extensible The S language is often the vehicle of choice for research in statistical methodology and R provides an Open Source route to participation in that activity One of R s strengths is the ease with which well designed publication quality plots can be produced including mathematical symbols and formulae where needed Great care has been taken over the defaults for the minor design choices in graphics but the user retains full control R is available as Free Software under the terms of the Free Software Foundation s GNU General Public License in source code form It compiles and runs on a wide variety of UNIX platforms and similar systems including FreeBSD and Linux Windows and MacOS The R environment R is an integrated suite of software facilities for data manipulation calculation and graphical display It includes an effective data handling and storage facility a suite of operators for calculations on arrays in particular matrices a large coherent integrated collection of intermediate tools for data analysis graphical facilities for data analysis and display either on screen or on hardcopy and a well developed simple and effective programming language which includes conditionals loops user defined recursive functions and input and output facilities The term environment is intended to characterize it as a fully planned and coherent system rather than an incremental accretion of very specific and inflexible tools as is frequently the case with other data analysis software R like S is designed around a true

    Original URL path: http://www.opus-project.fr/index.php/anropusproject?el_mcal_month=2&el_mcal_year=2016 (2016-01-11)
    Open archived version from archive

  • Home page
    22 November 2009 21 10 Author Administrator What is Opus The aim of OPUS Open source Platform for Uncertainty treatment in Simulation project is to create and sustain an activity around Generic Uncertainty Treatments by building and maintaining a reference tool for uncertainty treatment as well as providing a community friendly environment and extensive user contribution opportunities OPUS gathers 10 industrial and research partners and receives governmental funding via Agence Nationale pour la Recherche More Contributing to Opus Another goal of the project is the building of an active community centered around a forum and user made contributions written for the platform More Download contributions OPUS Final Report The final project report is available for download OPUS Final workshop Computer experiments and uncertainty analysis Friday October 21 2011 Henri Poincaré Institute 11 rue Pierre et Marie Curie Paris Click here for more details in French News Planning New publications Downloads Organisation Planning The workshop Calcul haute performance environnements de calcul et logiciels applications à la quantification d incertitudes will be held on 2011 03 22 in Grenoble in the laboratory Jean Kuntzmann New publications News publications are on line Using R features from Opus and Using Nisp from Opus Downloads

    Original URL path: http://www.opus-project.fr/index.php/index.php (2016-01-11)
    Open archived version from archive