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        Chapter Magnetic Iron Oxide Colloids for Environmental Applications 

        Alvaro, Gallo-Cordova; Almeida, Streitwieser; María, del Puerto Morales; G. Ovejero, Jesús (2021)
        This chapter deals with magnetic colloids with catalytic properties for the treatment of polluted waters and the efficient production of fuel alternatives. This kind of materials presents great advantages such as high ...
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        Chapter Management of Wine Aroma Compounds: Principal Basis and Future Perspectives 

        G. Pereira, Antia; Jesus, Simal-Gandara; Maria, Fraga; Paula, Garcia-Oliveira; Maria, Carpena; Cecilia, Jimenez-Lopez; Catarina, Lourenço-Lopes; Lillian, Barros; C.F.R. Ferreira, Isabel; Angel, Prieto (2020)
        Wine’s aroma is defined by volatile and non-volatile compounds that contribute to its make-up. The complex variety of volatile compounds, coming from grapes, interact with other non-volatile substances of the wine as ...
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        Chapter Opportunities of Circular Economy in a Complex System of Woody Biomass and Municipal Sewage Plants 

        Attila, Bai; Zoltán, Gabnai (2021)
        In this chapter, we present the opportunities and general importance of woody biomass production (forests and short-rotation coppices) and waste management in a common system. Wastewater and different forms of sewage sludge, ...
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        Chapter Operationalizing Heterogeneous Data-Driven Process Models for Various Industrial Sectors through Microservice-Oriented Cloud-Based Architecture 

        Valdemar, Lipenko; Sebastian, Nigl; Andreas, Roither-Voigt; Zelenay, David (2021)
        Industrial performance optimization increasingly makes the use of various analytical data-driven models. In this context, modern machine learning capabilities to predict future production quality outcomes, model predictive ...
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        Chapter Machine Learning Models for Industrial Applications 

        Enislay, Ramentol; Tomas, Olsson; Shaibal, Barua (2021)
        More and more industries are aspiring to achieve a successful production using the known artificial intelligence. Machine learning (ML) stands as a powerful tool for making very accurate predictions, concept classification, ...
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        Chapter xCARE: A Development Platform for Supporting Smart and Pervasive Healthcare 

        Eloisa, Vargiu; Meritxell, Gómez-Martínez; Silvia, Orte; Laura, Ros-Freixedes; Kian, Seif; David, Marí; Felip, Miralles (2021)
        We are assisting to an important change in the healthcare domain where healthy citizens and patients are more and more in the center and become active partners in the entire process. In this scenario, smart and pervasive ...
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        Chapter A Framework for Learning System for Complex Industrial Processes 

        Rahman, Moksadur; Fentaye, Amare Desalegn; Zaccaria, Valentina; Aslanidou, Ioanna; Dahlquist, Erik; Kyprianidis, Konstantinos (2021)
        Due to the intense price-based global competition, rising operating cost, rapidly changing economic conditions and stringent environmental regulations, modern process and energy industries are confronting unprecedented ...
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        Chapter Quality of Information within Internet of Things Data 

        Tomás, Alcañiz; Aurora, González-Vidal; P. Ramallo, Alfonso; F. Skarmeta, Antonio (2021)
        Due to the increasing number of IoT devices, the amount of data gathered nowadays is rather large and continuously growing. The availability of new sensors presented in IoT devices and open data platforms provides new ...
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        Chapter Evolving Roles of Spontaneous Reporting Systems to Assess and Monitor Drug Safety 

        Cosimo Antonazzo, Ippazio; Salvo, Francesco; Raschi, Emanuel; Pariente, Antoine; Moretti, Ugo; Poluzzi, Elisabetta; De Ponti, Fabrizio (2019)
        This chapter aims to describe current and emerging roles of spontaneous reporting systems (SRSs) for assessing and monitoring drug safety. Moreover, it offers a perspective on the near future, which entails the so-called ...
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        Chapter Power Struggles in the Management of Wildlife Resources: The Case of Burunge Wildlife Management Area, Tanzania 

        Mombo, Felister; Kicheleri, Rose P.; Nielsen, Martin; Treue, Thorsten; Kajembe, George C. (2019)
        Through a cross-sectional research design, this study examined power struggles in Burunge Wildlife Management Area (WMA) in Tanzania. Four out of ten villages comprising the WMA were purposively selected, and data were ...
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        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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