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Browsing by Author "Almeida, Rui"

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  • Multiple robot operations for maritime search and rescue in euRathlon 2015 competition
    Publication . Matos, Aníbal; Martins, Alfredo; Dias, André; Ferreira, Bruno; Almeida, José Miguel; Ferreira, Hugo; Amaral, Guilherme; Figueiredo, André; Almeida, Rui; Silva, Filipe
    This paper presents results of the INESC TEC participation in the maritime environment (both at surface and underwater) integrated in the ICARUS team in the euRathlon 2015 robotics search and rescue competition. These relate to the marine robots from INESC TEC, surface (ROAZ USV) and underwater (MARES AUV) autonomous vehicles participation in multiple tasks such as situation assessment, underwater mapping, leak detection or victim localization. This participation was integrated in the ICARUS Team resulting of the EU funded project aimed to develop robotic tools for large scale disasters. The coordinated search and rescue missions were performed with an initial surface survey providing data for AUV mission planning and execution. A situation assessment bathymetry map, sidescan sonar imaging and location of structures, underwater leaks and victims were achieved, with the global ICARUS team (involving sea, air and land coordinated robots) participating in the final grand Challenge and achieving the second place.
    2016Journal article Restricted access Show more
  • Using data mining with time series data in short-term stocks prediction
    Publication . Azevedo, Jose Manuel; Almeida, Rui; Almeida, Pedro
    Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series data, focusing on short- time stocks prediction. This is an area that has been attracting a great deal of attention from researchers in the field. The main contribution of this paper is to provide an outline of the use of DM with time series data, using mainly examples related with short-term stocks prediction. This is important to a better understanding of the field. Some of the main trends and open issues will also be introduced.
    2012-10Journal article Open access Show more