El presente artículo expone la crítica de Putnam sobre la noción de "referencia" en Fodor. Tal noción supone analizar el uso de condicionales contrafácticos y el uso de relaciones de dependencia asimétrica que realiza Fodor en Psico-semántica. De acuerdo con la concepción de Putnam, lo que se propone Fodor es naturalizar el discurso semántico-intencional; esto es, de lo que se trata es de ofrecer una reducción de la relación de referencia que no recurra a términos semántico-intencionales. Putnam concluye que no (...) es posible definir el léxico intencional en términos de un léxico no intencional porque el mero hecho de intentar tal reducción supone ya ejercitar un interés: la intención reductora. This article talks about the Putnam¿s critique to Fodor¿s reference notion. This notion means analysing counter factuals conditionals and the use of asymmetric dependence relations which Fodor translates into psycho semantic. According to Putnam¿s view, what Fodor¿s wants is to naturalize the semantic-intentional language. More precisely, Fodor offers a reduction of the reference relation that doesn¿t resort to semantic-intentional notions. Putnam concludes that it¿s not possible to define the intentional language in terms of a non intentional language because the simple fact of trying such a reduction implies the exercise of an intention: the reducer intention. (shrink)

Purpose The purpose of this study is to analyze how embedding of self-powered wireless sensors into cloud computing further enables such a system to become a sustainable part of work environment. Design/methodology/approach This is exemplified by an application scenario in healthcare that was developed in the context of the OpSIT project in Germany. A clearly outlined three-layer architecture, in the sense of Internet of Things, is presented. It provides the basis for integrating a broad range of sensors into smart healthcare (...) infrastructure. More specifically, by making use of short-range communication sensors, gateways which implement data transmission and low-level computation and cloud computing for processing the data. Findings A technical in-depth analysis of the first two layers of the infrastructure is given to prove reliability and to determine the communication quality and availability in real-world scenarios. Furthermore, two example use-cases that directly apply to a healthcare environment are examined, concluding with the feasibility of the presented approach. Practical implications Finally, the next research steps, oriented towards the semantic tagging and classification of data received from sensors, and the usage of advanced artificial intelligence-based algorithms on this information to produce useful knowledge, are described together with the derived social benefits. Originality/value The work presents an innovative, extensible and scalable system, proven to be useful in healthcare environments. (shrink)