Search results for "NETWORKS"
showing 10 items of 3260 documents
Análisis de las métricas alternativas de Archivos de Bronconeumología durante el periodo 2014-2018
2020
Introduction: Alternative metrics or altmetrics are non-traditional measurements of scientific production that reflect a publication's influence in social networks and similar channels of dissemination. The aim of this study was to analyze the media impact of ARCHIVOS DE BRONCONEUMOLOGÍA according to 2 altmetric aggregators and website visits. Methods: This was an observational study of the original articles and review and consensus articles published in ARCHIVOS DE BRONCONEUMOLOGÍA during the period 2014-2018. Data from the PlumX Metrics and Altmetric aggregators and visits to the ARCHIVOS DE BRONCONEUMOLOGÍA website were analyzed. Five comparisons were made: by specialty area, by funding …
An Intelligent System for Energy Efficiency in a Complex of Buildings
2012
Energy efficiency has nowadays become one of the most challenging task for both academic and commercial organizations, and this has boosted research on novel fields, such as Ambient Intelligence. In this paper we address the issue of timely and ubiquitous monitoring of building complexes in order to optimize their energy consumption, and present an intelligent system addressed to the typical end user, i.e. the administrator, or responsible operator, of the complex. A three-level architecture has been designed for detecting the presence of the building inhabitants user and understanding their preferences with respect to the environmental conditions in order to optimize the overall energy eff…
An AmI-Based Software Architecture Enabling Evolutionary Computation in Blended Commerce: The Shopping Plan Application
2015
This work describes an approach to synergistically exploit ambient intelligence technologies, mobile devices, and evolutionary computation in order to support blended commerce or ubiquitous commerce scenarios. The work proposes a software architecture consisting of three main components: linked data for e-commerce, cloud-based services, and mobile apps. The three components implement a scenario where a shopping mall is presented as an intelligent environment in which customers use NFC capabilities of their smartphones in order to handle e-coupons produced, suggested, and consumed by the abovesaid environment. The main function of the intelligent environment is to help customers define shopp…
Multi-sensor Fusion through Adaptive Bayesian Networks
2011
Common sensory devices for measuring environmental data are typically heterogeneous, and present strict energy constraints; moreover, they are likely affected by noise, and their behavior may vary across time. Bayesian Networks constitute a suitable tool for pre-processing such data before performing more refined artificial reasoning; the approach proposed here aims at obtaining the best trade-off between performance and cost, by adapting the operating mode of the underlying sensory devices. Moreover, self-configuration of the nodes providing the evidence to the Bayesian network is carried out by means of an on-line multi-objective optimization.
Polar bosons in one-dimensional disordered optical lattices
2013
We analyze the effects of disorder and quasi-disorder on the ground-state properties of ultra-cold polar bosons in optical lattices. We show that the interplay between disorder and inter-site interactions leads to rich phase diagrams. A uniform disorder leads to a Haldane-insulator phase with finite parity order, whereas the density-wave phase becomes a Bose-glass at very weak disorder. For quasi-disorder, the Haldane insulator connects with a gapped generalized incommesurate density wave without an intermediate critical region.
Machine Learning-Based Classification of Vector Vortex Beams.
2020
Structured light is attracting significant attention for its diverse applications in both classical and quantum optics. The so-called vector vortex beams display peculiar properties in both contexts due to the non-trivial correlations between optical polarization and orbital angular momentum. Here we demonstrate a new, flexible experimental approach to the classification of vortex vector beams. We first describe a platform for generating arbitrary complex vector vortex beams inspired to photonic quantum walks. We then exploit recent machine learning methods -- namely convolutional neural networks and principal component analysis -- to recognize and classify specific polarization patterns. O…
Mitigating DDoS using weight‐based geographical clustering
2020
Distributed denial of service (DDoS) attacks have for the last two decades been among the greatest threats facing the internet infrastructure. Mitigating DDoS attacks is a particularly challenging task as an attacker tries to conceal a huge amount of traffic inside a legitimate traffic flow. This article proposes to use data mining approaches to find unique hidden data structures which are able to characterize the normal traffic flow. This will serve as a mean for filtering illegitimate traffic under DDoS attacks. In this endeavor, we devise three algorithms built on previously uncharted areas within mitigation techniques where clustering techniques are used to create geographical clusters …
Solvent-free microwave-assisted extraction of polyphenols from olive tree leaves: Antioxidant and antimicrobial properties
2017
International audience; Response surface methodology (RSM) and artificial neural networks (ANN) were evaluated and compared in order to decide which method was the most appropriate to predict and optimize total phenolic content (TPC) and oleuropein yields in olive tree leaf (Olea europaea) extracts, obtained after solvent-free microwave- assisted extraction (SFMAE). The SFMAE processing conditions were: microwave irradiation power 250-350 W, extraction time 2-3 min, and the amount of sample 5-10 g. Furthermore, the antioxidant and antimicrobial activities of the olive leaf extracts, obtained under optimal extraction conditions, were assessed by several in vitro assays. ANN had better predic…
Comparative study to predict toxic modes of action of phenols from molecular structures.
2013
Quantitative structure-activity relationship models for the prediction of mode of toxic action (MOA) of 221 phenols to the ciliated protozoan Tetrahymena pyriformis using atom-based quadratic indices are reported. The phenols represent a variety of MOAs including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles and soft electrophiles. Linear discriminant analysis (LDA), and four machine learning techniques (ML), namely k-nearest neighbours (k-NN), support vector machine (SVM), classification trees (CTs) and artificial neural networks (ANNs), have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. M…
The HCV Sicily Network: A web-based model for the management of HCV chronic liver diseases
2016
Epidemiological studies report that in Sicily reside about 30,000 citizens with a diagnosis of chronic hepatitis due to HCV. The availability of direct antiviral action (DAA) is a real therapeutic breakthrough, but the high cost of the therapeutic regimes limits their use and forced the National Health System to establish clinical priority for the treatment.The HCV Sicily Network is a web-based model of best medical practice, which was designed to improve the management and the treatment of HCV chronic hepatitis and cirrhosis. The network includes 41 centers and 84 gastroenterologists or infectivologists connected by a web platform that recorder the diagnosis and the clinic priority for the…