L'influenza della preferenza manuale nell'interpretazione di conferenza: un contributo sperimentale

This study is based on a former student’s work, aimed at examining the influence of handedness on conference interpreting. In simultaneous interpreting (IS) both cerebral hemispheres participate in the decoding of the incoming message and in the activation of the motor functions for the production of the output signal. In right-handers language functions are mainly located in the left hemisphere, while left-handers have a more symmetrical representation of language functions. Given that with the development of interpreting skills and a long work experience the interpreters’ brain becomes less lateralized for language functions, in an initial phase left-handers may be «neurobiologically better suited for interpreting tasks» (Gran and Fabbro 1988: 37). To test this hypothesis, 9 students (5 right-handers and 4 left-handers) participated in a dual test of simultaneous and consecutive interpretation (CI) from English into Italian. The subjects were asked to interpret one text with their preferred ear and the other with the non-preferred one, since according neuropsychology aural symmetry reflects cerebral symmetry. The aim of this study was to analyze:1) the differences between the number of errors in consecutive and simultaneous interpretation with the preferred and non-preferred ear; 2) the differences in performance (in terms of number of errors) between right-handed and left-handed, both with the preferred and non-preferred ear; 3) the most frequent types of errors in right and left-handers; 4) the influence of the degree of handedness on interpreting quality. The students’ performances were analyzed in terms of errors of meaning, errors of numbers, omissions of text, omissions of numbers, inaccuracies, errors of nexus, and unfinished sentences. The results showed that: 1) in SI subjects committed fewer errors interpreting with the preferred ear, whereas in CI a slight advantage of the non-preferred ear was observed. Moreover, in CI, right-handers committed fewer mistakes with the non-preferred ear than with the preferred one. 2) The total performance of left-handers proved to be better than that of right-handers. 3) In SI left-handers committed fewer errors of meaning and fewer errors of number than right-handers, whereas in CI left-handers committed fewer errors of meaning and more errors of number than right-handers 4) As the degree of left-handedness increases, the number of errors committed also increases. Moreover, there is a statistically significant left-ear advantage for right-handers and a right-ear one for left-handers. Finally, those who interpreted with their right ear committed fewer errors of number than those who have used their left ear or both ears.

A framework for cyber-physical system simulation

In these last years, systems engineering has became one of the major research domains. The complexity of systems has increased constantly and nowadays Cyber-Physical Systems (CPS) are a category of particular interest: these, are systems composed by a cyber part (computer-based algorithms) that monitor and control some physical processes. Their development and simulation are both complex due to the importance of the interaction between the cyber and the physical entities: there are a lot of models written in different languages that need to exchange information among each other. Normally people use an orchestrator that takes care of the simulation of the models and the exchange of informations. This orchestrator is developed manually and this is a tedious and long work. Our proposition is to achieve to generate the orchestrator automatically through the use of Co-Modeling, i.e. by modeling the coordination. Before achieving this ultimate goal, it is important to understand the mechanisms and de facto standards that could be used in a co-modeling framework. So, I studied the use of a technology employed for co-simulation in the industry: FMI. In order to better understand the FMI standard, I realized an automatic export, in the FMI format, of the models realized in an existing software for discrete modeling: TimeSquare. I also developed a simple physical model in the existing open source openmodelica tool. Later, I started to understand how works an orchestrator, developing a simple one: this will be useful in future to generate an orchestrator automatically.