1,720,964 research outputs found
Enhanced Healthcare Environment by Means of Proactive Context Aware Service Discovery
No full textContext aware computing attains environments monitoring by means of sensors in order to provide relevant information or services according to the identified context. Nowadays, ad hoc wireless sensor networks for medical purposes are playing an increasing role within healthcare. Specifically, Body Sensor Networks (BSN) and Wireless Sensor Network, are being designed for prophylactic and follow-up monitoring of patients e. g., at home, at hospital, and so on. This work defines a framework aimed at proactively providing personalized healthcare services by performing sensor data analysis in order to recognize specific user's context. In particular, the approach is strongly based on the synergy between semantic formalisms and soft computing techniques. Semantic Web formalisms are exploited to model healthcare services and context. Soft computing techniques are applied in order to support activity of unsupervised context analysis and semantic service matchmaking. Specifically, Fuzzy Logic enable us to automatically characterize the context and to consequently find the set of healthcare services among the available ones that approximately meet the user's context. Experimental results shows performance in terms of services matchmaking
Hybrid approach for context-aware service discovery in healthcare domain
No full textContext-awareness computing is a research field which often refers to healthcare as an interesting and rich area of application. Context aware computing attains environments monitoring by means of sensors to provide relevant information or services according to the identified context. In particular, wireless ad hoc sensor networks for medical purposes are playing an increasing role within healthcare. Body Sensor Networks (BSN) are being designed for prophylactic and follow-up monitoring of patients in e.g. their homes, during hospitalization, and in emergencies. This work presents an integrated environment aimed at providing personalized healthcare services which appropriately meet the user@?s context. Deploying the semantics embedded in web services and context models is a mandatory step in the automation of service discovery, invocation and composition. Nevertheless, in a context aware domain purely logic-based reasoning on respectively context and services may not be enough. The main idea of this work is related to enrich with qualitative representation of context underling data by means of Fuzzy Logic in order to automatically recognize the context and to consequently find the right set of healthcare services among the available ones. Semantic formalisms (e.g., OWL, OWL-S, etc.) enable the context and services modeling in terms of domain ontology concepts. On the other hand, soft computing techniques support activity of unsupervised context analysis and healthcare semantic service discovery. Goal is to define context-aware system whose quality of retrieved services relies on the acquisition of user context by means of a robust theoretical approach. Moreover, this work defines hybrid architecture which attains a synergy between the agent-based paradigm and the fuzzy modeling. Specifically, the system exploits some task oriented agents in order to achieve context recognition, services matchmaking and brokerage activities
Swarm-based approach to evaluate fuzzy classification of semantic sensor data2012 IEEE International Conference on Pervasive Computing and Communications Workshops
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Swarm-based semantic fuzzy reasoning for situation awareness computing2012 IEEE International Conference on Fuzzy Systems
No full textSituation awareness computing employs sensor networks to collect large amounts of heterogeneous data in different and complex environments. The rapid development and deployment of sensor technology stress the problem related to the availability of too much and heterogeneous data. Last trend emphasizes the semantic annotation of acquired sensor data. Semantic sensor data provides machine understandable contextual information. In particular, the availability of semantic sensor data allows situation awareness in several application domains. This paper introduces a swarm-based approach to semantic web reasoning in order to identify situations. On one hand, fuzzy control has been employed in order to face with uncertainty of happening situations. On the other hand, Situation Theory has been used in order to model situation awareness. A multi agent swarm architecture enables to monitor complex environments by using spatially distributed autonomous sensors. An application scenario for bank intrusion detection has been described
f-SPARQL extension and application to support context recognition2012 IEEE International Conference on Fuzzy Systems
No full textContext aware computing as well as wearable and ubiquitous computing often attain with pattern recognition on incoming sensor data. Recognizing more (useful) contexts requires more information about the context, and thus more sensors and better recognition algorithms. In order to enable logic inference on incoming data, the proposed work assumes that incoming data are represented by means of semantic languages (e.g., RDF, OWL, etc.). Nevertheless, in a context aware computing purely logic-based reasoning on context may not be enough. So, the work introduces soft computing techniques to approximate context recognition. Specifically, this paper introduces an approach to context analysis and recognition that relies on f-SPARQL[1] tool, that is a flexible extension of SPARQL. In particular, in this work a JAVA implementation of f-SPARQL and the integrated support for fuzzy clustering and classification are discussed. This tool is exploited in the architecture that foresees some task oriented agents in order to achieve context analysis and recognition in order to identify critical situations. Finally, a simple application scenario and preliminary experimental results have been described
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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