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SPARKLE - Entrepreneurship for Sustainable Precision Agriculture (SPA) is a course aiming to increase 'agripreneurship' among students, entrepreneurs and academics, enhancing knowledge and skills on technologies, innovations, entrepreneurial thinking and problem-solving skills into the farming sector. It also aims to transform the agricultural sector into a SPA-oriented system that could build an innovative ecosystem of agripreuners and agritechnicians around agriculture and entrepreneurship. The course is divided into four areas (SPA Overview, Technologies, Social and economic aspects and entrepreneurship in agriculture), 12 lessons and 55 topics leads students on a path for deepening the knowledge in a comprehensive system where technologies are a piece of the whole structure.

Sustainable Precision Agriculture --- Smart Farming --- Lean Management --- Entrepreneurship in Agriculture

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SPARKLE - Entrepreneurship for Sustainable Precision Agriculture (SPA) is a course aiming to increase 'agripreneurship' among students, entrepreneurs and academics, enhancing knowledge and skills on technologies, innovations, entrepreneurial thinking and problem-solving skills into the farming sector. It also aims to transform the agricultural sector into a SPA-oriented system that could build an innovative ecosystem of agripreuners and agritechnicians around agriculture and entrepreneurship. The course is divided into four areas (SPA Overview, Technologies, Social and economic aspects and entrepreneurship in agriculture), 12 lessons and 55 topics leads students on a path for deepening the knowledge in a comprehensive system where technologies are a piece of the whole structure.

Sustainable Precision Agriculture --- Smart Farming --- Lean Management --- Entrepreneurship in Agriculture

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Large-scale agribusinesses are among the largest and oldest oligopoly corporations in the world, now constituting a form of big tech alongside companies like Google and Facebook. The Immaculate Conception of Data explores the secretive legal agreements surrounding agricultural big data to trace how it is used and with what consequences.

Agriculture --- Data processing. --- Economic aspects. --- 4. --- AI. --- Big Tech. --- Big. --- John Deere. --- Monsanto. --- UAV. --- activist. --- agribusiness. --- agriculture. --- agroecological. --- algorithm. --- artificial intelligence. --- bias. --- concentration. --- corporate. --- critical studies. --- digital. --- drone. --- ethnography. --- farm. --- farmer. --- food. --- future. --- industrial agriculture. --- inequity. --- open. --- organic. --- power. --- precision analytics. --- private. --- productivism. --- public. --- science. --- sensor. --- smart farming. --- system. --- technology. --- technopolitics. --- tractor. --- unethical. --- unsustainable. --- values.

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Data science is an emerging multidisciplinary field which lies at the intersection of computer science, statistics, and mathematics, with different applications and related to data mining, deep learning, and big data. This Special Issue on “Principles and Applications of Data Science” focuses on the latest developments in the theories, techniques, and applications of data science. The topics include data cleansing, data mining, machine learning, deep learning, and the applications of medical and healthcare, as well as social media.

Technology: general issues --- History of engineering & technology --- deep learning --- user preference learning --- feature fusion --- similar user recommendation --- convolutional neural network --- image classification --- electronic health records --- fair exchange --- forward secrecy --- raw material --- mining --- terminology --- dictionary --- terminology application --- mobile application --- digitization --- lexical data --- corpus data --- linguistic linked open data --- neuro-fuzzy --- prediction model --- air pollution --- PM2.5 --- PM10 --- self-attention mechanism --- graph neural network --- data mining --- behaviour sequence pattern --- behaviour network --- water crystal --- fine-tuning --- supervised --- classification --- combined classification model --- deep transfer learning --- focal-segmental --- kidney disease --- kidney glomeruli --- medical image --- sclerosed glomeruli --- predictive analytics --- Internet of Things --- peasant farming --- smart farming system --- crop production prediction

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Data science is an emerging multidisciplinary field which lies at the intersection of computer science, statistics, and mathematics, with different applications and related to data mining, deep learning, and big data. This Special Issue on “Principles and Applications of Data Science” focuses on the latest developments in the theories, techniques, and applications of data science. The topics include data cleansing, data mining, machine learning, deep learning, and the applications of medical and healthcare, as well as social media.

Technology: general issues --- History of engineering & technology --- deep learning --- user preference learning --- feature fusion --- similar user recommendation --- convolutional neural network --- image classification --- electronic health records --- fair exchange --- forward secrecy --- raw material --- mining --- terminology --- dictionary --- terminology application --- mobile application --- digitization --- lexical data --- corpus data --- linguistic linked open data --- neuro-fuzzy --- prediction model --- air pollution --- PM2.5 --- PM10 --- self-attention mechanism --- graph neural network --- data mining --- behaviour sequence pattern --- behaviour network --- water crystal --- fine-tuning --- supervised --- classification --- combined classification model --- deep transfer learning --- focal-segmental --- kidney disease --- kidney glomeruli --- medical image --- sclerosed glomeruli --- predictive analytics --- Internet of Things --- peasant farming --- smart farming system --- crop production prediction