A SIFT-Based Fingerprint Verification System Using Cellular Neural Networks

Recently, with the increasing demand of high security, person identification has become more and more important in our everyday life. The purpose of establishing the identity is to ensure that only a legitimate user, and not anyone else, accesses the rendered services. The traditional identification methods are based on “something that you possess ” and “somethin

Adult listening behaviour, music preferences and emotions in the mobile context. Does mobile context affect elicited emotions?

After the introduction of mobile computing devices, the way people listen to music has changed considerably. Although there is a broad scientific consensus on the fact that people show music preferences and make music choices based on their feelings and emotions, the sources of such preferences and choices are still debated. The main aim of this study is to understand whether listening in ecological (mobile) contexts differs from listening in non-mobile contexts in terms of the elicited emotive response. A total of 328 participants listen to 100 classical music tracks, available through an ad-hoc mobile application for mobile devices. The participants were asked to report their self-evaluation of each of the tracks, according to the Pleasure-Arousal-Dominance model and filled out a questionnaire about their listening behaviour. Our findings show that the same factors that affect music listening in non-mobile contexts also affect it in a mobile context

Prioritization-based Bandwidth Allocation for MOST networks

Abstract The Media Oriented Systems Transport (MOST

Remote Eye-Tracking for Cognitive Telerehabilitation and Interactive School Tasks in Times of COVID-19

In the attempt to mitigate the effects of COVID-19 lockdown, most countries have recently authorized and promoted the adoption of e-learning and remote teaching technologies, often with the support of teleconferencing platforms. Unfortunately, not all students can benefit from the adoption of such a surrogate of their usual school. We were asked to devise a way to allow a community of children affected by the Rett genetic syndrome, and thus unable to communicate verbally, in writing or by gestures, to actively participate in remote rehabilitation and special education sessions by exploiting eye-gaze tracking. As not all subjects can access commercial eye-tracking devices, we investigated new ways to facilitate the access to eye gaze-based interaction for this specific case. The adopted communication platform is a videoconferencing software, so all we had at our disposal was a live video stream of the child. As a solution to the problem, we developed a software (named SWYG) that only runs at the “operator” side of the communication, at the side of the videoconferencing software, and does not require to install other software in the child’s computer. The preliminary results obtained are very promising and the software is ready to be deployed on a larger base. While this paper is being written, several children are finally able to communicate with their caregivers from home, without relying on expensive and cumbersome devices

Improving the Reader’s Attention and Focus through an AI-Driven Interactive and User-Aware Virtual Assistant for Handheld Devices

This paper describes the design and development of an AI-driven, interactive and user-aware virtual assistant aimed at helping users to focus their attention on reading or attending to other long-lasting visual tasks. The proposed approach uses computer vision and artificial intelligence to analyze the orientation of the head and the gaze of the user’s eyes to estimate the level of attention during the task, as well as administer effective and balanced stimuli to correct significant deviations. The stimuli are provided by a graphical character (i.e., the virtual assistant), which is able to emulate face expressions, generate spoken messages and produce deictic visual cues to better involve the user and establish an effective, natural and enjoyable experience. The described virtual assistant is based on a modular architecture that can be scaled to support a wide range of applications, from virtual and blended collaborative spaces to mobile devices. In particular, this paper focuses on an application designed to integrate seamlessly into tablets and e-book readers to provide its services in mobility and exactly when and where needed

The TCTRS Project: A Holistic Approach for Telerehabilitation in Rett Syndrome

Telerehabilitation (TR) has been proven to be an effective tool in improving the adaptive skills of children and young adults with Multiple Disabilities (MDs). The application of a comprehensive set of new technologies reveals new opportunities for both physical and cognitive telerehabilitation, but there is no holistic approach in the case of genetic syndromes. In this paper we present reflections and early results of the TCTRS project that aims at implementing a telerehabilitation system capable of offering complete coverage of rehabilitation needs for people with Rett Syndrome, from both the physical and cognitive points of view. Moreover, the data acquired through the system can also represent a basis for machine learning applications to remotely support therapists and physicians. Our first tests on the system application show the great potential of our approach, in terms of feasibility and applicability, for both rehabilitation centers and families

A Perspective on Passive Human Sensing with Bluetooth

Passive human sensing approaches based on the analysis of the radio signals emitted by the most common wireless communication technologies have been steadily gaining momentum during the last decade. In this context, the Bluetooth technology, despite its widespread adoption in mobile and IoT applications, so far has not received all the attention it deserves. However, the introduction of the Bluetooth direction finding feature and the application of Artificial Intelligence techniques to the processing and analysis of the wireless signal for passive human sensing pave the way for novel Bluetooth-based passive human sensing applications, which will leverage Bluetooth Low Energy features, such as low power consumption, noise resilience, wide diffusion, and relatively low deployment cost. This paper provides a reasoned analysis of the data preprocessing and classification techniques proposed in the literature on Bluetooth-based remote passive human sensing, which is supported by a comparison of the reported accuracy results. Building on such results, the paper also identifies and discusses the multiple factors and operating conditions that explain the different accuracy values achieved by the considered techniques, and it draws the main research directions for the near future