Vicent Costa

This work focuses on the virtual museum, understood as the digital transformation of the traditional museum. First, the main conceptualizations of the virtual museum in the specialized literature are reviewed, and based on them, we propose a basic definition. Furthermore, we argue in favor of the insufficiency of the dataist perspective in the study of epistemic injustice associated with the virtual museum. Finally, the exclusion related to the participation and interaction between a museum’s visitors and the institution is analyzed. Este trabajo se centra en el museo virtual entendido como la transformación digital del museo tradicional. En primer lugar, se revisan las principales conceptualizaciones del museo virtual en la literatura especializada y, a partir de las mismas, se propone una definición básica. Asimismo, se presentan argumentos que muestran la insuficiencia de la perspectiva dataísta en el estudio de la injusticia epistémica relativa al museo virtual. Finalmente, se analiza la exclusión relativa a la participación y la interacción entre las visitantes de un museo (tanto virtual como físico) y la propia institución.

This paper presents a logical Style painting classifier based on evaluated Horn clauses, qualitative colour descriptors and Explanations. Three versions of $\ell $-SHE are defined, using rational Pavelka logic, and expansions of Gödel logic and product logic with rational constants: RPL, $G$ and $\sqcap $, respectively. We introduce a fuzzy representation of the more representative colour traits for the Baroque, the Impressionism and the Post-Impressionism art styles. The $\ell $-SHE algorithm has been implemented in Swi-Prolog and tested on 90 paintings of the QArt-Dataset and on 247 paintings of the Paintings-91-PIB dataset. The percentages of accuracy obtained in the QArt-Dataset for each $\ell $-SHE version are 73.3%, 65.6% $) and 68.9% $). Regarding the Paintings-91-PIB dataset, the percentages of accuracy obtained for each $\ell $-SHE version are 60.2%, 48.2% $) and 57.0% $). Our logic definition for the Baroque style has obtained the highest accuracy in both datasets, for all the $\ell $-SHE versions. An important feature of the classifier is that it provides reasons regarding why a painting belongs to a certain style. The classifier also provides reasons about why outliers of one art style may belong to another art style, giving a second classification option depending on its membership degrees to these styles.

This paper is a contribution to graded model theory, in the context of mathematical fuzzy logic. We study characterizations of classes of graded structures in terms of the syntactic form of their first-order axiomatization. We focus on classes given by universal and universal-existential sentences. In particular, we prove two amalgamation results using the technique of diagrams in the setting of structures valued on a finite MTL-algebra, from which analogues of the Łoś–Tarski and the Chang–Łoś–Suszko preservation theorems follow.