DrawSE2: an application for the visual definition of visual languages using the local context-based visual language specification

We present DrawSE2, a new web application that allows the definition of visual languages in a more visual way (according to the local context-based visual language specification). The tool allows the user to create visual language elements, define their attaching areas (the hotspots through which language elements can be connected), and define how they can be linked together to form admissible language sentences. The tool also allows semantic attributes to be defined and enables semantic translation (e.g., to a textual representation). The visual language thus defined can then be used in a diagram editor that allows to draw visual sentences of the language, check their correctness and get their semantic translation

IFree: Design and evaluation of a pointing method for disabled users on mobile devices

We present the design and evaluation of a pointing method for disabled people, called iFree, which can run on mobile devices such as smartphones and tablets. The method is based on face recognition and supports target selection (click) in two different modes: by opening and closing the mouth (mouth click) and by making a sound (sound click).The method was experimented on a smartphone with 14 non-disabled participants in order to evaluate its performance and to compare the two above mentioned modes. In particular, we measured its performance using ISO 9241-411 standard task. The throughput grand mean was 0.86 bit/s. The sound click mode had a greater throughput and accuracy, a lower movement time and was preferred by participants

Co-authorship networks and scientific performance of Italian academic statisticians

The aim of this paper is to explore the effect of the use of three data sources \u2013Web of Science, Current Index to Statistics and nationally funded research projects\u2013 on the analysis of co-authorship networks among Italian academic statisticians. Results provide evidence of our hypotheses on distinct collaboration patterns among statisticians, as well as distinct effects of scientist network positions on scientific performance, by both Statistics subfield and data source