e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.

This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.

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Title

Developing Mobile Intelligent System For Cattle Disease Diagnosis and First Aid Action Suggestion

en
Abstract

Animal husbandry is one of main concerns of agricultural development revitalization in Indonesia. The domestic products from this sector are yet to meet the domestics' demands of meat and dairy products. Therefore, instead of continuously dependent on imported products, efforts on animal husbandry revitalization to stimulate the production growth from this sector are critically needed. The aim of this paper is to present the work of developing mobile intelligent system for cattle diseases diagnosis and first aid action suggestion system. The core intelligent engine of the system is developed using fuzzy neural network. In the sense of ubiquity of smartphones, the user interface is developed as mobile application under Android operating system. System testing over real-world cattle diagnosis medical data set and expert verification showed that the systems could diagnose correctly with validity 100% and average accuracy 96.37%. The experimental results also showed that frame base knowledge representation outperformed rule base knowledge representation.

en
Year
2013
en
Country
  • ID
Organization
    Data keywords
    • knowledge
    • knowledge representation
    en
    Agriculture keywords
    • cattle
    • agriculture
    en
    Data topic
    • information systems
    • sensors
    en
    SO
    2013 SEVENTH INTERNATIONAL CONFERENCE ON COMPLEX, INTELLIGENT, AND SOFTWARE INTENSIVE SYSTEMS (CISIS)
    Document type

    Inappropriate format for Document type, expected simple value but got array, please use list format

    Institutions 10 co-publis
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      e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
      Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.