A novel method for validating multi-classifiers. A case study for ICF-based health status classification

In this paper, we propose a novel method for the validation of a multi-classification model according to the intended use and aim of a device for health status classification and the clinical needs of the practitioners involved

A computational framework to support the treatment of bedsores during COVID-19 diffusion

The treatment of pressure ulcers, also known as bedsores, is a complex process that requires to employ specialized field workforce assisting patients in their houses. In the period of COVID-19 or during any other non-trivial emergency, reaching the patients in their own house is impossible. Therefore, as well as in the other sectors, the adoption of digital technologies is invoked to solve, or at least mitigate, the problem. In particular, during the COVID-19, the social distances should be maintained in order to decrease the risk of contagion. The Project Health Management Systems proposes a complete framework, based on Deep Learning, Augmented Reality. Pattern Matching, Image Segmentation and Edge Detection approaches, to support the treatment of bedsores without increasing the risk of contagion, i.e., improving the remote aiding of specialized operators and physicians and involving inexperienced familiars in the process

Understanding the composition and evolution of terrorist group networks: A rough set approach

Nowadays, many resources for counter-terrorism operations are available for researchers belonging to different areas. In particular, the START project provides the Global Terrorism Database (GTD) that can be analyzed in order to provide, for instance, prediction models. The main idea underlying this work is using the historical data provided by GTD, which offers information related to terrorist attacks perpetrated since 1970, in order to conceptualize the behaviors of terrorist groups in specific time intervals. Such conceptualizations are, subsequently, used to understand the similarity between terrorist groups and elicit relations to represent terrorists' networks. The above networks can be used to study the temporal evolutions of terrorist groups' behaviors by applying the approach in different time periods along the timeline and studying differences among the resulting networks. The approach is mainly based on Rough Set Theory and Three-way Decisions Theory and provides an original similarity function based on the definition of boundary regions. (C) 2019 Elsevier B.V. All rights reserved

A virtual counselor for online social networks (or did I really want to send you my post?)

It is well established by the scientific literature that a great part of Face-to-Face communication occurs at a non verbal level and also that this is partly obfuscated when the interaction takes place by Computer-Mediated-Communication (CMC). Fully aware we are simplifying the subject, we can say that the communication satisfies the need of humans to share their emotional experiences. Thus we can say that also the formulation and interpretation of messages exchanged in CMC is influenced by the emotions. Moreover the reduced physical presence in CMC implies a lack of social norms or social control which is amplified in the Online Social Networks (OSN) scenario. Motivated by these naïve considerations and the massive use of OSN, we introduce a Virtual Counselor as a contribution, from a technical point of view, to augment the quality of communication among users of OSN. The implementation of this Virtual Counselor is based on technologies by now mature like wearable devices to measure physical parameters, on artificial emotional intelligence, and on interactive tutoring systems, strongly used in online learning environments. We propose an abstract model of the communication scenario in OSN containing the Virtual Counselor to help the interpretation of the messages and of the emotional states in order to improve the communication among parties. The goal is to align the emotional states of senders and receivers to form dynamic groups of target friends in the OSN to send the posts to. The dynamism of the groups is both spatial (that is the composition of receivers can change for a given sender and a given message) and temporal (for example the sending of a message can be postponed in time). We think that this model is the basis for defining a new class of tools to improve the communication in OSN

A comprehensive model and computational methods to improve Situation Awareness in Intelligence scenarios

This paper presents a comprehensive model for representing and reasoning on situations to support decision makers in Intelligence analysis activities. The main result presented in the paper stems from a work of refinement and abstraction of previous results of the authors related to the use of Situation Awareness and Granular Computing for the development of analysis methods and techniques to support Intelligence. This work made it possible to derive the characteristics of the model from previous case studies and applications with real data, and to link the reasoning techniques to concrete approaches used by intelligence analysts such as, for example, the Structured Analytic Techniques. The model allows to represent an operational situation according to three complementary perspectives: descriptive, relational and behavioral. These three perspectives are instantiated on the basis of the principles and methods of Granular Computing, mainly based on the theories of fuzzy and rough sets, and with the help of further structures such as graphs. As regards the reasoning on the situations thus represented, the paper presents four methods with related case studies and applications validated on real data

Solving the shopping plan problem through bio-inspired approaches

Blended commerce involves all commerce experiences in which customers make use of different channels (online, offline and mobile) for their purchases to take advantages with respect to their needs and attitudes. This new e-commerce trend is typically characterized by so-called loyalty programmes such as coupons and system points. These mechanisms can be extremely useful for the companies to achieve customer retention and for the customers to obtain discounts. However, loyalty programmes can complicate for customers the evaluation of all offers and the selection of optimal providers (shopping plan) for buying the desired set of products. To face this problem, referred as Shopping Plan Problem, optimization algorithms are emerging as a suitable methodology. This paper is aimed at performing a systematic comparison amongst three bio-inspired optimization approaches, genetic algorithms, memetic ones and ant colony optimization, to detect the best performer for solving the shopping plan problem in a blended shopping scenario. © 2015 Springer-Verlag Berlin HeidelbergBlended commerce involves all commerce experiences in which customers make use of different channels (online, offline and mobile) for their purchases to take advantages with respect to their needs and attitudes. This new e-commerce trend is typically characterized by so-called loyalty programmes such as coupons and system points. These mechanisms can be extremely useful for the companies to achieve customer retention and for the customers to obtain discounts. However, loyalty programmes can complicate for customers the evaluation of all offers and the selection of optimal providers (shopping plan) for buying the desired set of products. To face this problem, referred as Shopping Plan Problem, optimization algorithms are emerging as a suitable methodology. This paper is aimed at performing a systematic comparison amongst three bio-inspired optimization approaches, genetic algorithms, memetic ones and ant colony optimization, to detect the best performer for solving the shopping plan problem in a blended shopping scenario

An emotion-driven virtual counselling system in computer-mediated communication

We present and evaluate a virtual counselling system that is devoted to improving user awareness of emotional situations in computer-mediated communication and making informed decisions on actions to recommend to the users involved in a conversation. Starting from elements such as the moods and emotions of the users involved in a conversation, the system constructs the emotional signatures of individuals and groups that are used to characterize a situation. It then uses an approximate reasoning mechanism based on three-way decisions to classify recognized situations with respect to particular emotional dynamics based on emotional contagion. A prototype of the system has been experimented on in a real context based on collaboration between university students for the realization of project work. The distinctive features of the system have been evaluated with accuracy measures, and the results are promising