9 resultados para Web Semantico semantic open data geoSPARQL
em Universidade do Minho
Resumo:
FOSTER aims to support different stakeholders, especially young researchers, in adopting open access in the context of the European Research Area (ERA) and in complying with the open access policies and rules of participation set out for Horizon 2020 (H2020). FOSTER establish a European-wide training programme on open access and open data, consolidating training activities at downstream level and reaching diverse disciplinary communities and countries in the ERA. The training programme includes different approaches and delivery options: elearning, blearning, self-learning, dissemination of training materials/contents, helpdesk, face-to-face training, especially training-the-trainers, summer schools, seminars, etc.
Resumo:
O projeto FOSTER – Facilitate Open Science Training for European Research é uma iniciativa que pretende apoiar diferentes intervenientes envolvidos no processo de comunicação científica, principalmente jovens investigadores. Este apoio visa a adoção do Acesso Aberto no contexto do Espaço Europeu da Investigação (EEI) e a conformidade com as políticas de Acesso Aberto e com as regras de participação do Horizonte 2020 (H2020). Para atingir este objetivo, o FOSTER, pretende focar-se na integração dos princípios e práticas de Acesso Aberto no atual sistema de investigação e contribuir para o desenvolvimento de sessões de formação nas instituições que realizam investigação científica de forma a manter níveis de conformidade satisfatórios com as políticas de Acesso Aberto no EEI e H2020. Para tal, tem desenvolvido um programa de formação sobre Acesso Aberto e dados abertos para consolidar as atividades de formação dirigidas a diversas comunidades e países do EEI. Este programa propõe incluir pacotes de formação que incluam aconselhamento, apoio técnico na utilização de sistemas e-learning, b-learning e de autoformação, disponibilização de materiais/conteúdos, sessões presenciais, principalmente formação de formadores, escolas de verão, seminários, etc.
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Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação
Resumo:
Tese de Doutoramento em Ciências da Educação (área de especialização em Tecnologia Educativa)
Resumo:
OpenAIRE supports the European Commission Open Access policy by providing an infrastructure for researchers to comply with the European Union Open Access mandate. The current OpenAIRE infrastructure and services, resulting from OpenAIRE and OpenAIREplus FP7 projects, builds on Open Access research results from a wide range of repositories and other data sources: institutional or thematic publication repositories, Open Access journals, data repositories, Current Research Information Systems and aggregators. (...)
Resumo:
This research aims to advance blinking detection in the context of work activity. Rather than patients having to attend a clinic, blinking videos can be acquired in a work environment, and further automatically analyzed. Therefore, this paper presents a methodology to perform the automatic detection of eye blink using consumer videos acquired with low-cost web cameras. This methodology includes the detection of the face and eyes of the recorded person, and then it analyzes the low-level features of the eye region to create a quantitative vector. Finally, this vector is classified into one of the two categories considered —open and closed eyes— by using machine learning algorithms. The effectiveness of the proposed methodology was demonstrated since it provides unbiased results with classification errors under 5%
Resumo:
Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores
Resumo:
Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.
Resumo:
The Smart Drug Search is publicly accessible at http://sing.ei.uvigo.es/sds/. The BIOMedical Search Engine Framework is freely available for non-commercial use at https://github.com/agjacome/biomsef