دانلود مقاله انگلیسی رایگان:زیرساخت داده های بزرگ برای بازسازی تصاویر توموگرافی کشاورزی - 2018
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دانلود مقاله انگلیسی داده های بزرگ رایگان
  • Big Data infrastructure for agricultural tomographic images reconstruction Big Data infrastructure for agricultural tomographic images reconstruction
    Big Data infrastructure for agricultural tomographic images reconstruction

    سال انتشار:

    2018


    عنوان انگلیسی مقاله:

    Big Data infrastructure for agricultural tomographic images reconstruction


    ترجمه فارسی عنوان مقاله:

    زیرساخت داده های بزرگ برای بازسازی تصاویر توموگرافی کشاورزی


    منبع:

    IEEE - 2018 12th IEEE International Conference on Semantic Computing


    نویسنده:

    Gabriel M. Alves†*, Paulo E. Cruvinel*†


    چکیده انگلیسی:

    A single agricultural soil sample obtained by a tomograph is composed of too many projections. In addition, considering that a sample is scanned at different angles a big set of projections is formed. Therefore, when using micro-resolution tomographic instruments, for a single soil sample it is necessary to deal with amounts of data in the order of gigabytes. On the other hand, the quantity of samples contributes to quality of information, for example, in the construction of maps to study agricultural soils. In general, in order to get improvements in the quality of soil analyzes it is required to increase exponentially the amount of the soil samples, i. e., increasing the amount of data to be reconstructed, which exceed the order of terabytes. This massive amount of data suggests new emerging methods and technologies. In this sense, Big Data has shown the great potential in optimizing data, making decisions, spotting business trends in various fields such agriculture. In this work, the infrastructure for the process of tomographic reconstruction of agricultural soil samples based on Big Data is presented. We introduced the Big Data architecture which uses the Hadoop framework. Additionally, we present the Filtered Back-Projection (FBP) algorithm adapted to the MapReduce model. The use of Big Data environment allows reconstructing a greatest number of agricultural soil tomographic images in the same time-frame and, consequently, it allows increasing the number of analysis contributing to improvement of quality of information about agricultural soils. Furthermore, the developed application has required both interpretation and language generation to allow the organization of knowledge, as well as the establishment of an adequate computational semantics for its operation.
    Keywords: big data, infrastructure, semantics in big data, agricultural tomograph, apache hadoop


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 6
    حجم فایل: 248 کیلوبایت

    قیمت: رایگان


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