A Complementary Account to Emotion Extraction and Classification in Cultural Heritage Based on the Plutchik’s Theory

The paper presents a combined approach to knowledge-based emotion attribution and classification of cultural items employed in the H2020 project SPICE. In particular, we show a preliminary experimentation conducted on a selection of items contributed by the GAM Museum in Turin (Galleria di Arte Moderna), pointing out how different language-based approaches to emotion categorization (used in the systems Sophia and DEGARI respectively) can be powerfully combined to cope with both coverage and extended affective attributions. Interestingly, both approaches are based on an ontology of the Plutchik’s theory of emotions

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Reconocimiento de imágenes de flora y fauna

Desarrollo de un método de identificación de especies de fauna y flora a partir de imágenes. Se han usado métodos de deep learning teniendo en cuenta las características de la taxonomía de cada especie

An Agent Based Autonomic Semantic Platform

In 2001, two distinct revolutionary approaches to distributed system integration and web content diffusion were proposed: Autonomic Computing and the Semantic Web. These approaches are currently two of the most active research fields in the information technology area. After three years, many common themes came out: while Autonomic Computing research is focused on providing ways to define “self-surviving ” systems, the Semantic Web struggles to define web content semantics producing complex and distributed services on the Internet. In a sense, the first area approaches systems defining the “internal, operational knowledge”, while the second defines the knowledge about the environment into which software entities and humans should cohabit. This paper lies in the convergence of the two approaches and proposes an agent-based system able to semantically characterize and search a set of web resources, and to maintain and update its knowledge base by means of monitoring sensors and interaction with external web services. First experimental results confirm the validity of the combined approach in terms of search recall, thanks to autonomous update of covered topics. 1