Typing your mind away. Comparing keylogged tasks with the Task Segment Framework

One of the main process features under study in Cognitive Translation & Interpreting Studies (CTIS) is the chronological unfolding of the tasks. The analyses of time spans in translation have been conceived in two ways: (1) studying those falling between text units of different sizes: words, phrases, sentences, and paragraphs; (2) setting arbitrary time span thresholds to explore where do they fall in the text, whether between text units or not. Writing disfluencies may lead to comprehensive insights into the cognitive activities involved in typing while translating. Indeed, long time spans are often taken as hints that cognitive resources have been subtracted from typing and devoted to other activities, such as planning, evaluating, etc. This exploratory, pilot study combined both approaches to seek potential general tendencies and contrasts in informants’ inferred mental processes when performing different writing tasks, through the analysis of their behaviors, as keylogged. The study tasks were retyping, monolingual free writing, translation, revision and a multimodal task—namely, monolingual text production based on an infographic leaflet. Task logs were chunked, and shorter time spans, including those within words, were analyzed following the Task Segment Framework (Muñoz & Apfelthaler, in press). Finally, time span analysis was combined with the analysis of the texts as to their lexical density, type-token ratio and word frequency. Several previous results were confirmed, and some others were surprising. Time spans in free writing were longer between paragraphs and sentences, possibly hinting at planning and, in translation, between clauses and words, suggesting more cognitive activities at these levels. On the other hand, the infographic was expected to facilitate the writing process, but most time spans were longer than in both free writing and translation. Results of the multimodal task and some other results suggest venues for further research.

Big data analytics and modeling for Human Mobility

The fast development of Information Communication Technologies (ICT) offers new opportunities to realize future smart cities. To understand, manage and forecast the city's behavior, it is necessary the analysis of different kinds of data from the most varied dataset acquisition systems. The aim of this research activity in the framework of Data Science and Complex Systems Physics is to provide stakeholders with new knowledge tools to improve the sustainability of mobility demand in future cities. Under this perspective, the governance of mobility demand generated by large tourist flows is becoming a vital issue for the quality of life in Italian cities' historical centers, which will worsen in the next future due to the continuous globalization process. Another critical theme is sustainable mobility, which aims to reduce private transportation means in the cities and improve multimodal mobility. We analyze the statistical properties of urban mobility of Venice, Rimini, and Bologna by using different datasets provided by companies and local authorities. We develop algorithms and tools for cartography extraction, trips reconstruction, multimodality classification, and mobility simulation. We show the existence of characteristic mobility paths and statistical properties depending on transport means and user's kinds. Finally, we use our results to model and simulate the overall behavior of the cars moving in the Emilia Romagna Region and the pedestrians moving in Venice with software able to replicate in silico the demand for mobility and its dynamic.

La dimensione interazionale nell'interpretazione di conferenza: il caso dell'interpretazione consecutiva tra l'italiano e il cinese in conferenze con minor grado di formalità

La nascita dell’interpretazione di conferenza è strettamente legata a storici incontri diplomatici e ai congressi di istituzioni internazionali di grande rilievo. Tuttavia, oggi, nell’epoca della globalizzazione, ci si riunisce sempre più per la condivisione di conoscenze e per motivi personali, anche in contesti meno formalizzati. Sebbene, in quanto conferenza, le norme interazionali continuino a vincolare il meccanismo dei turni di parola, in tali circostanze tra l’oratore e chi lo ascolta si instaurano maggiore sintonia e attenzione reciproca attraverso molteplici mezzi comunicativi, verbali e non-verbali. Il presente studio, posizionandosi nella prospettiva dell’analisi discorsiva e della comunicazione multimodale, ha come obiettivo quello di verificare se la presenza dell’interprete modifichi la relazione interpersonale caratterizzata dal senso di reciprocità tra chi enuncia e chi ascolta, e se sì, quali siano le nuove dinamiche comunicative che emergono. A tal fine, sono stati reperiti filmati di nove conferenze con minor grado di formalità dove era previsto lo svolgimento dell’interpretazione consecutiva tra l’italiano e il cinese e, relativamente a questi, sono state eseguite dapprima due fasi di valutazione preliminare: la prima prevedeva la raccolta e l’analisi delle informazioni di base riguardanti lo svolgimento dei nove eventi e i relativi partecipanti; la seconda consisteva nell’esame contrastivo tra i sistemi linguistico-culturali italiano e cinese. In seguito all’acquisizione delle informazioni contestuali e circostanziali, si è proceduto all’analisi qualitativa dei casi di studio di interazione tra l’interprete e gli altri partecipanti. A tal fine, soni stati esaminati non solo gli interventi linguistici, ma anche le attività non-verbali. Nonostante la molteplicità delle dinamiche osservate, è stato possibile riconoscere una tendenza secondo cui l’interprete stabilisce relazioni di carattere dialogico sia con i partecipanti presenti sul palco, ovvero l’oratore e il moderatore, che con il pubblico presente agli eventi analizzati.

[In search of] Digital biomarkers for objective pain assessment

Pain is a highly complex phenomenon involving intricate neural systems, whose interactions with other physiological mechanisms are not fully understood. Standard pain assessment methods, relying on verbal communication, often fail to provide reliable and accurate information, which poses a critical challenge in the clinical context. In the era of ubiquitous and inexpensive physiological monitoring, coupled with the advancement of artificial intelligence, these new tools appear as the natural candidates to be tested to address such a challenge. This thesis aims to conduct experimental research to develop digital biomarkers for pain assessment. After providing an overview of the state-of-the-art regarding pain neurophysiology and assessment tools, methods for appropriately conditioning physiological signals and controlling confounding factors are presented. The thesis focuses on three different pain conditions: cancer pain, chronic low back pain, and pain experienced by patients undergoing neurorehabilitation. The approach presented in this thesis has shown promise, but further studies are needed to confirm and strengthen these results. Prior to developing any models, a preliminary signal quality check is essential, along with the inclusion of personal and health information in the models to limit their confounding effects. A multimodal approach is preferred for better performance, although unimodal analysis has revealed interesting aspects of the pain experience. This approach can enrich the routine clinical pain assessment procedure by enabling pain to be monitored when and where it is actually experienced, and without the involvement of explicit communication,. This would improve the characterization of the pain experience, aid in antalgic therapy personalization, and bring timely relief, with the ultimate goal of improving the quality of life of patients suffering from pain.

On making web accessibility more accessible: strategy and tools for social good

The world currently faces a paradox in terms of accessibility for people with disabilities. While digital technologies hold immense potential to improve their quality of life, the majority of web content still exhibits critical accessibility issues. This PhD thesis addresses this challenge by proposing two interconnected research branches. The first introduces a groundbreaking approach to improving web accessibility by rethinking how it is approached, making it more accessible itself. It involves the development of: 1. AX, a declarative framework of web components that enforces the generation of accessible markup by means of static analysis. 2. An innovative accessibility testing and evaluation methodology, which communicates test results by exploiting concepts that developers are already familiar with (visual rendering and mouse operability) to convey the accessibility of a page. This methodology is implemented through the SAHARIAN browser extension. 3. A11A, a categorized and structured collection of curated accessibility resources aimed at facilitating their intended audiences discover and use them. The second branch focuses on unleashing the full potential of digital technologies to improve accessibility in the physical world. The thesis proposes the SCAMP methodology to make scientific artifacts accessible to blind, visually impaired individuals, and the general public. It enhances the natural characteristics of objects, making them more accessible through interactive, multimodal, and multisensory experiences. Additionally, the prototype of \gls{a11yvt}, a system supporting accessible virtual tours, is presented. It provides blind and visually impaired individuals with features necessary to explore unfamiliar indoor environments, while maintaining universal design principles that makes it suitable for usage by the general public. The thesis extensively discusses the theoretical foundations, design, development, and unique characteristics of these innovative tools. Usability tests with the intended target audiences demonstrate the effectiveness of the proposed artifacts, suggesting their potential to significantly improve the current state of accessibility.

Urban air mobility: modelling the future transport system

The advances in the aviation field, particularly the development of electric flying vehicles, as UAV and eVTOL, paved the way for setting Urban Air Mobility (UAM) services. UAM would provide services for passengers, goods and emergencies and could offer faster trips than ground ones. It is expected that early UAM operations will be performed at Very Low-Level airspace as 0-500 m Above Ground Level. The purpose of this research is to both explore the main features of UAM and test an aerial network model, which could be integrated in a multimodal transport system where ground and aerial mobility services are provided. Analyses on UAM transport system involved two sub-systems: the transport demand sub-system, i.e., the mobility requirements, and the transport supply sub-system, i.e., the service and facilities enabling mobility. At first, the UAM demand levels and features for an Airport Shuttle service have been explored through a suitable survey, by combining Revealed and Stated Preference methodologies, and by calibrating some discrete mode choice models. Then, the focus has been on the transport supply model for UAM services, by focusing on both the ground access points (vertiports) and the aerial network model. A suitable three-dimensional urban aerial network (3D-UAN) model that could support fast aerial connections between O/D pairs has been proposed. Some tests have been implemented to verify the feasibility of the proposed model. Some flying vehicles supporting an Airport Shuttle service have been simulated on the aerial network, which has been specified in terms of both topological features and link transport costs. The preliminary results have showed that the proposed 3D-UAN model could be suitable for supporting UAM services. As for transport engineering, the UAM system framework proposed in this thesis paves the way for further research on air-ground multimodality in urban areas.

Assessing the Environmental Performance of New Mobility

This report has two main goals. First to improve methodologies of new mobility services .Second identify the solution to improve new mobility in urban transportation to decrease energy loss and decline climate change. This report also compares energy use and greenhouse gasses (GHG) emission impact for new mobility and all transportation modes. Having focus on central estimates and a range of possible alternatives to enhance the result to advance environmental effects. This analysis and research help to identify the possible solutions to make new mobility more sustainable