Training and modernisation of public administrations and services – SATDAP – Training of Public Administration (Q2913535): Difference between revisions

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(‎Removed claim: budget (P474): 234,600.0 euro)
(‎Changed an Item: modifying budgets in portugal one item from slovenia)
Property / budget
 
276,000.0 Euro
Amount276,000.0 Euro
UnitEuro
Property / budget: 276,000.0 Euro / rank
 
Normal rank
Property / EU contribution
 
234,600.0 Euro
Amount234,600.0 Euro
UnitEuro
Property / EU contribution: 234,600.0 Euro / rank
 
Normal rank
Property / co-financing rate
 
85.0 percent
Amount85.0 percent
Unitpercent
Property / co-financing rate: 85.0 percent / rank
 
Normal rank

Revision as of 23:08, 21 October 2021

Project Q2913535 in Portugal
Language Label Description Also known as
English
Training and modernisation of public administrations and services – SATDAP – Training of Public Administration
Project Q2913535 in Portugal

    Statements

    contained in NUTS
    Ave
    0 references
    country
    Portugal
    0 references
    EU contribution
    234,600.0 Euro
    0 references
    budget
    276,000.0 Euro
    0 references
    co-financing rate
    85.0 percent
    0 references
    start time
    1 November 2019
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    end time
    31 October 2021
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    beneficiary name (string)
    HOSPITAL DA SENHORA DA OLIVEIRA GUIMARÃES, E. P. E.
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    beneficiary
    Q3002115
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    fund
    European Social Fund
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    coordinate location

    41°26'30.37"N, 8°17'44.05"W
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    summary
    A presente Operação a que o HSOG se candidata, em estreita colaboração com a comunidade científica, pretende promover a transferência de conhecimento e a adoção de técnicas avançadas de inteligência artificial e ciência dos dados, com o objetivo de criar modelos de previsão que possibilitem a identificação atempada de infeções de forma automática. (Portuguese)
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    This Operation to which HSOG is a candidate, in close collaboration with the scientific community, aims to promote the transfer of knowledge and the adoption of advanced techniques of artificial intelligence and data science, with the aim of creating prediction models that enable the timely identification of infections automatically. (English)
    point in time
    8 July 2021
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    location (string)
    Guimarães
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    Identifiers

    Portuguese Kohesio ID
    POCI-05-5762-FSE-000209
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