Voice assistants in hospital triage operations

This paper analyzes the creation and usage of a voice assistant for the triage of emergency room patients. This human-centred intelligent system strongly relies on Mycroft, an extensible open source voice assistant. The patients are able to declare their symptoms to the agent, which recognizes the urgency and acts accordingly. The software can even provide useful medical informations to the users

Emotion-based analysis of programming languages on Stack Overflow

When developing a software engineering project, selecting the most appropriate programming language is a crucial step. Most often, feeling at ease with the possible options becomes almost as relevant as the technical features of the language. Therefore, it appears to be worth analyzing the role that the emotional component plays in this process. In this article, we analyze the trend of the emotions expressed by developers in 2018 on the Stack Overflow platform in posts concerning 26 programming languages. To do so, we propose a learning model trained by distant supervision and the comparison of two different classifier architectures

Mobility in Unsupervised Word Embeddings for Knowledge Extraction—The Scholars’ Trajectories across Research Topics

In the knowledge discovery field of the Big Data domain the analysis of geographic positioning and mobility information plays a key role. At the same time, in the Natural Language Processing (NLP) domain pre-trained models such as BERT and word embedding algorithms such as Word2Vec enabled a rich encoding of words that allows mapping textual data into points of an arbitrary multi-dimensional space, in which the notion of proximity reflects an association among terms or topics. The main contribution of this paper is to show how analytical tools, traditionally adopted to deal with geographic data to measure the mobility of an agent in a time interval, can also be effectively applied to extract knowledge in a semantic realm, such as a semantic space of words and topics, looking for latent trajectories that can benefit the properties of neural network latent representations. As a case study, the Scopus database was queried about works of highly cited researchers in recent years. On this basis, we performed a dynamic analysis, for measuring the Radius of Gyration as an index of the mobility of researchers across scientific topics. The semantic space is built from the automatic analysis of the paper abstracts of each author. In particular, we evaluated two different methodologies to build the semantic space and we found that Word2Vec embeddings perform better than the BERT ones for this task. Finally, The scholars’ trajectories show some latent properties of this model, which also represent new scientific contributions of this work. These properties include (i) the correlation between the scientific mobility and the achievement of scientific results, measured through the H-index; (ii) differences in the behavior of researchers working in different countries and subjects; and (iii) some interesting similarities between mobility patterns in this semantic realm and those typically observed in the case of human mobility

Cellular automata based inverse perspective transform as a tool for indoor robot navigation

In this paper we describe a system for perspective-effect removal using the cellular automata paradigm. The system has been developed as a tool to be included in the vision system of an autonomous robot designed to operate in indoor environments. The navigation of such a robot is guided by traffic signs by means of a neural-network based system. By using such a tool as part of the vision system, it is possible to instruct the neural networks with a training set including only frontal views of the signs, thus simplifying training and making it computationally much lighter. Furthermore, using a low-cost massively parallel architecture implementing the cellular automata paradigm, makes the algorithm much more computationally efficient with respect to sequential implementations, thus making it possible for the robot to perform just-in-time operations

Adoption of social media in socio-technical systems: A survey

This article describes the current landscape in the fields of social media and socio-technical systems. In particular, it analyzes the different ways in which social media are adopted in organizations, workplaces, educational and smart environments. One interesting aspect of this integration, is the use of social media for members’ participation and access to the processes and services of their organization. Those services cover many different types of daily routines and life activities, such as health, education, transports. In this survey, we compare and classify current research works according to multiple features, including: the use of Social Network Analysis and Social Capital models, users’ motivations for participation and organizational costs, adoption of the social media platform from below. Our results show that many of these current systems are developed without taking into proper consideration the social structures and processes, with some notable and positive exceptions