Very large irregular-grid volume data sets are typically represented as tetrahedral mesh and require substantial disk I/O and rendering computation. One effective way to reduce this demanding resource requirement is compression. Previous research showed how rendering and decompression of a losslessly compressed irregular-grid data set can be integrated into a one-pass computation. This work adv...

We present a new Lexical Simplification approach that exploits Neural Networks to learn substitutions from the Newsela corpus a large set of professionally produced simplifications. We extract candidate substitutions by combining the Newsela corpus with a retrofitted context-aware word embeddings model and rank them using a new neural regression model that learns rankings from annotated data. T...

In this paper we present the results of a study directed towards developing a lexical simplification module of an automatic simplification system for Spanish, intended for readers with cognitive disabilities. We here observe the word length and frequency distribution of two sets of texts that make up our parallel corpus, and we focus on cases of information expansion (through the insertion of d...

We describe two systems for text simplification using typed dependency structures, one that performs lexical and syntactic simplification, and another that performs sentence compression optimised to satisfy global text constraints such as lexical density, the ratio of difficult words, and text length. We report a substantial evaluation that demonstrates the superiority of our systems, individua...

Meshes are currently used to model objects, namely human organs and other structures. However, if they have a large number of triangles, their rendering times may not be adequate to allow interactive visualization, a mostly desirable feature in some diagnosis (or, more generally, decision) scenarios, where the choice of adequate views is important. In this case, a possible solution consists in ...

Text simplification is the process of changing vocabulary and grammatical structure to create a more accessible version of the text while maintaining the underlying information and content. Automated tools for text simplification are a practical way to make large corpora of text accessible to a wider audience lacking high levels of fluency in the corpus language. In this work, we investigate th...

In this paper, we present design and construction of the first Italian corpus for automatic and semi–automatic text simplification. In line with current approaches, we propose a new annotation scheme specifically conceived to identify the typology of changes an original sentence undergoes when it is manually simplified. Such a scheme has been applied to two aligned Italian corpora, containing o...