Search results for "Casting"

2017

Abstract. Polycyclic aromatic hydrocarbons (PAHs) are hazardous pollutants, with increasing emissions in pace with economic development in East Asia, but their distribution and fate in the atmosphere are not yet well understood. We extended the regional atmospheric chemistry model WRF-Chem (Weather Research Forecast model with Chemistry module) to comprehensively study the atmospheric distribution and the fate of low-concentration, slowly degrading semivolatile compounds. The WRF-Chem-PAH model reflects the state-of-the-art understanding of current PAHs studies with several new or updated features. It was applied for PAHs covering a wide range of volatility and hydrophobicity, i.e. phenanth…

Stochastic models for wind speed forecasting

2011

Abstract This paper is concerned with the problem of developing a general class of stochastic models for hourly average wind speed time series. The proposed approach has been applied to the time series recorded during 4 years in two sites of Sicily, a region of Italy, and it has attained valuable results in terms both of modelling and forecasting. Moreover, the 24 h predictions obtained employing only 1-month time series are quite similar to those provided by a feed-forward artificial neural network trained on 2 years data.

Looking over the channel: The balance of media coverage about the “refugee crisis” in Germany and the UK

2022

Abstract This study compares the balance of newspaper and television news coverage about migration in two countries that were differently affected by the so-called “refugee crisis” in 2015 in terms of the geopolitical involvement and numbers of migrants being admitted. Based on a broad consensus among political elites, Germany left its borders open and received about one million migrants mainly from Syria during 2015. In contrast, the conservative British government was heavily attacked by oppositional parties for closing Britain’s borders and, thus, restricting immigration. These different initial situations led to remarkable differences between the news coverage in both countries. In line…

Broadcasting Indigenous Voices

2008

Ethnic minority media embody much of the multiculturalist, multilingual and transnational changes in the media landscape and in the wider societal frame as well. Often minority media aim at providing relevant information, but also alternative publicity and empowering experiences in regard to their own identity, language and culture. Through an analysis of journalists' interviews and ethnographic data, this article examines how these tendencies, possibilities and limitations are played out in the indigenous Sami media. The findings suggest that the Sami journalists have managed to provide an alternative public space and contribute to linguistic revitalization. Yet, working within translocal …

Audiovisual Representation in Spanish and European Election Debates

2020

The presence of ever more conflicting stances between Europhiles and Eurosceptics has revealed some audiovisual discourses unknown until now. The fragmentation of inconclusive narrative discourse and staged situations with a clear intent to clash all make it necessary to analyse in detail the role given by the audiovisual media to the European process of democratisation. This study addresses the audiovisual discourse in Spanish public television (TVE) with the intention of discovering how the different topics addressed in debates are dealt with in audiovisual production, and whether those topics have benefited from certain decisions by the production team that are subjective a priori. Using…

Day-ahead forecasting for photovoltaic power using artificial neural networks ensembles

2016

Solar photovoltaic plants power output forecasting using machine learning techniques can be of a great advantage to energy producers when they are implemented with day-ahead energy market data. In this work a model was developed using a supervised learning algorithm of multilayer perceptron feedforward artificial neural network to predict the next twenty-four hours (day-ahead) power of a solar facility using fetched weather forecast of the following day. Each set of tested network configuration was trained by the historical power output of the plant as a target. For each configuration, one hundred networks ensembles was averaged to give the ability to generalize a better forecast. The train…

Unreliable predictions about COVID‐19 infections and hospitalizations make people worry: The case of Italy

2021

Methodological considerations for interrupted time series analysis in radiation epidemiology: an overview

2021

Interrupted time series analysis (ITSA) is a method that can be applied to evaluate health outcomes in populations exposed to ionizing radiation following major radiological events. Using aggregated time series data, ITSA evaluates whether the time trend of a health indicator shows a change associated with the radiological event. That is, ITSA checks whether there is a statistically significant discrepancy between the projection of a pre-event trend and the data empirically observed after the event. Conducting ITSA requires one to consider specific methodological issues due to unique threats to internal validity that make ITSA prone to bias. We here discuss the strengths and limitations of …

ADME Prediction with KNIME: Development and Validation of a Publicly Available Workflow for the Prediction of Human Oral Bioavailability.

2020

In silico prediction of human oral bioavailability is a relevant tool for the selection of potential drug candidates and for the rejection of those molecules with less probability of success during the early stages of drug discovery and development. However, the high variability and complexity of oral bioavailability and the limited experimental data in the public domain have mainly restricted the development of reliable in silico models to predict this property from the chemical structure. In this study we present a KNIME automated workflow to predict human oral bioavailability of new drug and drug-like molecules based on five machine learning approaches combined into an ensemble model. Th…

Predicting perceived visual complexity of abstract patterns using computational measures: The influence of mirror symmetry on complexity perception

2017

Visual complexity is relevant for many areas ranging from improving usability of technical displays or websites up to understanding aesthetic experiences. Therefore, many attempts have been made to relate objective properties of images to perceived complexity in artworks and other images. It has been argued that visual complexity is a multidimensional construct mainly consisting of two dimensions: A quantitative dimension that increases complexity through number of elements, and a structural dimension representing order negatively related to complexity. The objective of this work is to study human perception of visual complexity utilizing two large independent sets of abstract patterns. A w…