1,720,979 research outputs found
Design of an ambient intelligence services architecture for optimizing quality of service of message transmission in eHealth
La gestion de l'acheminement de messages d'e-santé en environnement ubiquitaire soulève plusieurs défis majeurs liés à la diversité et à la spécificité des cas d'usage et des acteurs, à l'évolutivité des contextes médical, social, logistique, environnemental...Nous proposons une méthode originale d'orchestration autonome et auto-adaptative de services visant à optimiser le flux des messages et à personnaliser la qualité de transmission, en les adressant aux destinataires les plus appropriés dans les délais requis. Notre solution est une architecture générique dirigée par des modèles du domaine d'information considéré et des données contextuelles, basés sur l'identification des besoins et des contraintes soulevées par notre problématique.Notre approche consiste en la composition de services de fusion et de gestion dynamique en temps réel d'informations hétérogènes provenant des écosystèmes source, cible et message, pilotés par des méthodes d'intelligence artificielle pour l'aide à la prise de décision de routage. Le but est de garantir une communication fiable, personnalisable et sensible à l'évolution du contexte, quel que soit le scénario et le type de message (alarme, technique, etc.). Notre architecture, applicable à divers domaines, a été consolidée par une modélisation des processus métiers (BPM) explicitant le fonctionnement des services qui la composent.Le cadriciel proposé est basé sur des ontologies et est compatible avec le standard HL7 V3. L'auto-adaptation du processus décisionnel d'acheminement est assurée par un réseau bayésien dynamique et la supervision du statut des messages par une modélisation mathématique utilisant des réseaux de Petri temporelsRouting policy management of eHealth messages in ubiquitous environment leads to address several key issues, such as taking into account the diversity and specificity of the different use cases and actors, as well as the dynamicity of the medical, social, logistic and environmental contexts.We propose an original, autonomous and adaptive service orchestration methodology aiming at optimizing message flow and personalizing transmission quality by timely sending the messages to the appropriate recipients. Our solution consists in a generic, model-driven architecture where domain information and context models were designed according to user needs and requirements. Our approach consists in composing, in real time, services for dynamic fusion and management of heterogeneous information from source, target and message ecosystems, driven by artificial intelligence methods for routing decision support. The aim is to ensure reliable, personalized and dynamic context-aware communication, whatever the scenario and the message type (alarm, technical, etc.). Our architecture is applicable to various domains, and has been strengthened by business process modeling (BPM) to make explicit the services operation.The proposed framework is based on ontologies and is compatible with the HL7 V3 standard. Self-adaptation of the routing decision process is performed by means of a dynamic Bayesian network and the messages status supervision is based on timed Petri net
Going Beyond Counting First Authors in Author Co-citation Analysis
The 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
“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
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
An ECG Web Services Portal for Standard and Serial ECG Analysis with Enhanced 3D Graphical Capabilities
False Alarm Reduction in Self-Care by Personalized Automatic Detection of ECG Electrode Cable Interchanges
Introduction. False alarm reduction is an important challenge in self-care, whereas one of the most important false alarm causes in the cardiology domain is electrodes misplacements in ECG recordings, the main investigations to perform for early and pervasive detection of cardiovascular diseases. In this context, we present and assess a new method for electrode reversals identification for Mason-Likar based 3D ECG recording systems which are especially convenient to use in self-care and allow to achieve, as previously reported, high computerized ischemia detection accuracy. Methods. We mathematically simulate the effect of the six pairwise reversals of the LA, RA, LL, and C2 electrodes on the three ECG leads I, II, and V2. Our approach then consists in performing serial comparisons of the newly recorded 3D ECG and of the six derived ECGs simulating an electrode reversal with a standard, 12-lead reference ECG by means of the CAVIAR software. We further use a scoring method to compare these analysis results and then apply a decision tree model to extract the most relevant measurements in a learning set of 121 patients recorded in ICU. Results. The comparison of the seven sets of serial analysis results from the learning set resulted in the determination of a composite criteria involving four measurements of spatial orientation changes of QRS and T and providing a reversal identification accuracy of 100%. Almost the same results, with 99.99% of sensitivity and 100% of specificity, were obtained in two test sets from 90 patients, composed of 2098 and 2036 representative ECG beats respectively recorded during PTCA balloon inflation, a procedure which mimics ischemia, and before PTCA for control. Conclusion. Personalized automatic detection of ECG electrode cable interchanges can reach almost the maximal accuracy of 100% in self-care, and can be performed in almost real time
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