Thirty years of artificial intelligence in medicine (AIME) conferences: A review of research themes

Over the past 30 years, the international conference on Artificial Intelligence in MEdicine (AIME) has been organized at different venues across Europe every 2 years, establishing a forum for scientific exchange and creating an active research community. The Artificial Intelligence in Medicine journal has published theme issues with extended versions of selected AIME papers since 1998

A Série Cornélio Pires: análise da forma musical das suas modas-de-viola

Resumo: O objetivo deste artigo é o de realizar uma análise da forma musical das primeiras modas-de-viola da história do disco no Brasil: aquelas gravadas pela Columbia sob o selo Cornélio Pires nos anos 1929 e 1930. A análise será feita com base num modelo estrutural que separa as partes geralmente presentes em uma moda-de-viola, aqui denominada de partes fixas, daquelas circunstanciais, mais flexíveis na estrutura das modas-de-viola e, consequentemente, sujeitas aos estilos dos compositores e aqui denominada de partes móveis ou opcionais. O conteúdo do presente artigo corresponde, portanto, a um exercício de análise das modas-de-viola da série Cornélio Pires com base neste modelo teórico gerando, de um lado, a compreensão das particularidades dessas modas-de-viola e, de outro, uma revisão crítica deste modelo teórico. Palavras-chave: Forma musical, Teoria musical, Moda-de-viola, Música caipira. Cornélio Pires.  Cornélio Pires Label: analysis of musical form of its modas-de-viola Abstract: The purpose of this article is to carry out an analysis of the musical form of the first modas-de-viola of the history in Brazil: those recorded by Columbia Records under the label Cornélio Pires in the years 1929 and 1930. The analysis will be based on a structural model that separates the parties usually always present in a moda-de-viola (the fixed parts) those circumstantial of this genre music and, consequently, resulting of the intentions and styles of composers (the optional parts). Therefore, the content of this article corresponds to a screening of analysis with modas-de-viola based on this theoretical model generating, on the one hand, understanding the particularities of these songs and, on the other hand, a critical review of this theoretical model in question.  Keywords: Musical Form. Moda-de-viola. Theory. Música caipira. Cornélio Pires.

A Novel Approach Based on a Hierarchical Multiresolution Analysis of Optical Time Series to Reconstruct the Daily High-Resolution Snow Cover Area

High-resolution (HR) snow cover maps derived by remotely sensed images are an asset for data assimilation in hydrological models. However, the current satellite missions do not provide daily HR multispectral observations suitable for an accurate snow monitoring in alpine environments. On the contrary, low-resolution (LR) sensors acquire daily information of snow cover fraction (SCF) but at an inappropriate spatial scale. This article proposes a novel approach that combines multisource and multiscale acquisitions to infer the daily HR snow cover area (SCA) for mountainous basins. The approach builds on the assumption that interannual snow patterns are both affected by the local geomorphometry and meteorology. We derive these patterns through a hierarchical multistep approach based on historical statistical analyses on a long and sparse HR time-series. At each step, we obtain HR snow cover maps with higher number of reconstructed pixels but decreasing level of confidence. Historical data are used to estimate the probability that a HR pixel is covered by snow according to two possible multiscale strategies: 1) HR gap-filling, or 2) LR downscaling. These analyses lead to the identification of the patterns that regularly appear given certain conditions. When no systematic patterns are observed, we reinforce the inference of the pixel class by a generalized additive model that exploits not only the historical data, but also explicit geomorphometric, global snow, and multitemporal properties. The proposed approach has been validated on a catchment in the Sierra Nevada, USA, for three hydrological years (2017–2019) showing an average overall accuracy of 92%

A Novel Data Fusion Technique for Snow Cover Retrieval

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents a novel data fusion technique for improving the snow cover monitoring for a mesoscale Alpine region, in particular in those areas where two information sources disagree. The presented methodological innovation consists in the integration of remote-sensing data products and the numerical simulation results by means of a machine learning classifier (support vector machine), capable to extract information from their quality measures. This differs from the existing approaches where remote sensing is only used for model tuning or data assimilation. The technique has been tested to generate a time series of about 1300 snow maps for the period between October 2012 and July 2016. The results show an average agreement between the fused product and the reference ground data of 96%, compared to 90% of the moderate-resolution imaging spectroradiometer (MODIS) data product and 92% of the numerical model simulation. Moreover, one of the most important results is observed from the analysis of snow cover area (SCA) time series, where the fused product seems to overcome the well-known underestimation of snow in forest of the MODIS product, by accurately reproducing the SCA peaks of winter season

Remaking Europe: the new manufacturing as an engine for growth. Bruegel Blueprint Series 26 September 2017

Europe needs to know how it can realise the potential for industrial rejuvenation. How well are European firms responding to the new opportunities for growth, and in which global value chains are they developing these new activities? The policy discussion on the future of manufacturing requires an understanding of the changing role of manufacturing in Europe’s growth agenda

Combined Use of Sentinel-1 and Sentinel-2 for Glacier Mapping: An Application Over Central East Alps

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Knowledge Management for Policy: Stocktaking of one year of JRC activities

Improving knowledge management and collaborative working is a priority for overcoming silos mentalities and connecting synergies between portfolios, as envisaged in the Commission Communication C(2016)6626. In its 2030 Strategy, the JRC took up this challenge by 1) introducing a horizontal ‘knowledge management’ layer in the organigram, to mobilise scientific competences from different Directorates around the Commission’s policy goals 2) championing the implementation of new collaboration practices and platforms as well as the development of a knowledge management professionalisation programme; 3) starting to transform itself from a traditional research-producing organisation into a world-leading manager of knowledge for EU policy-making. One year after the reorganisation carried out on the 1st of July 2016 to align the JRC organigram with the new strategy, this report reviews the progress made and describes the main achievements.JRC.H-Knowledge Management (Ispra

Ten principles to integrate the water-energy-land nexus with climate services for co-producing local and regional integrated assessments

The water-energy-land nexus requires long-sighted approaches that help avoid maladaptive pathways to ensure its promise to deliver insights and tools that improve policy-making. Climate services can form the foundation to avoid myopia in nexus studies by providing information about how climate change will alter the balance of nexus resources and the nature of their interactions. Nexus studies can help climate services by providing information about the implications of climate-informed decisions for other economic sectors across nexus resources. First-of-its-kind guidance is provided to combine nexus studies and climate services. The guidance consists of ten principles and a visual guide, which are discussed together with questions to compare diverse case studies and with examples to support the application of the principles

A Simulated Annealing Approach to Approximate Bayes Computations

Approximate Bayes Computations (ABC) are used for parameter inference when the likelihood function of the model is expensive to evaluate but relatively cheap to sample from. In particle ABC, an ensemble of particles in the product space of model outputs and parameters is propagated in such a way that its output marginal approaches a delta function at the data and its parameter marginal approaches the posterior distribution. Inspired by Simulated Annealing, we present a new class of particle algorithms for ABC, based on a sequence of Metropolis kernels, associated with a decreasing sequence of tolerances w.r.t. the data. Unlike other algorithms, our class of algorithms is not based on importance sampling. Hence, it does not suffer from a loss of effective sample size due to re-sampling. We prove convergence under a condition on the speed at which the tolerance is decreased. Furthermore, we present a scheme that adapts the tolerance and the jump distribution in parameter space according to some mean-fields of the ensemble, which preserves the statistical independence of the particles, in the limit of infinite sample size. This adaptive scheme aims at converging as close as possible to the correct result with as few system updates as possible via minimizing the entropy production in the system. The performance of this new class of algorithms is compared against two other recent algorithms on two toy examples.Comment: 20 pages, 2 figure