A5073949445- Human-Automation Interaction and Safety
- Sleep and Work-Related Fatigue
- Emotion and Mood Recognition
- Mobile Agent-Based Network Management
- Artificial Intelligence in Healthcare and Education
- Multimedia Communication and Technology
- IPv6, Mobility, Handover, Networks, Security
- Innovative Human-Technology Interaction
- Service-Oriented Architecture and Web Services
- Innovative Approaches in Technology and Social Development
- Network Traffic and Congestion Control
- Green IT and Sustainability
- Color perception and design
- Peer-to-Peer Network Technologies
- Software-Defined Networks and 5G
- User Authentication and Security Systems
- Spam and Phishing Detection
- Clinical Reasoning and Diagnostic Skills
- Medieval Architecture and Archaeology
- Healthcare Technology and Patient Monitoring
- Advanced Malware Detection Techniques
- Ancient Mediterranean Archaeology and History
- Behavioral Health and Interventions
- Digital Transformation in Industry
- Ethics and Social Impacts of AI
Università degli Studi Suor Orsola Benincasa
2016-2025
University of Naples Federico II
2011-2014
Advanced Driver-Assistance Systems (ADASs) are used for increasing safety in the automotive domain, yet current ADASs notably operate without taking into account drivers’ states, e.g., whether she/he is emotionally apt to drive. In this paper, we first review state-of-the-art of emotional and cognitive analysis ADAS: consider psychological models, sensors needed capturing physiological signals, typical algorithms human emotion classification. Our investigation highlights a lack advanced...
Behavioral changes are critical for addressing sustainability challenges, which have become increasingly urgent due to the growing impact of global greenhouse gas emissions on ecosystems and human livelihoods. However, translating awareness into meaningful action requires practical tools bridge this gap. Mobile applications, utilizing strategies from human–computer interaction (HCI) such as gamification, nudging, persuasive technologies, proven be powerful in promoting sustainable behaviors....
It has been shown that an increased mental workload in pilots could lead to a decrease their situation awareness, which lead, turn, worse piloting performance and ultimately critical human errors. Assessing the current pilot's psycho-physiological state is hot topic of interest for developing advanced embedded cockpits systems capable adapting behavior pilot. In this work, we investigate method classify different levels cognitive starting from synchronized EEG eye-tracking information. The...
With the integration of virtualization technologies, Internet Things (IoT) is expanding its capabilities and quickly becoming a complex ecosystem networked devices. The Social (SIoT), where intelligent things include social properties that improve functioning user engagement, result this progress. SIoT still has issues with scalability, data management, user-centric operations, despite tremendous In order to overcome these obstacles, strong architecture needed can handle enormous number IoT...
Several elements can affect the drivers' behaviour while they are performing driving activities. Ranging from visual to cognitive distractions, emotions and other conditions (that could emerge biometric data, such as temperature, heartbeat, pressure, etc.) play a significant role, factor that increase response time. This be crucial in avoiding dangerous situations deciding actions influence happening of car accidents. paper introduces concept "Fitness-to-Drive" index aims evaluate how...
This paper presents the design and implementation of CCMP, a conference management protocol currently under standardization within IETF, conceived at outset as lightweight allowing conferencing clients to access manipulate objects describing centralized conference. The CCMP is state-less, XML-based, client-server carrying in its request response messages information form XML documents fragments conforming data model schema. It represents powerful means control basic advanced features such...
The pervasiveness of phishing signals the insufficiency current measures. Through a multidisciplinary approach, we conducted an eye-tracking study on how and where users look when they have to classify email as or legitimate. Furthermore, investigated whether there is difference between expert non-expert subjects. showed firstly, better performance in recognising emails by experts. Secondly, eye movement data use different inspection methods experts non-experts. This could open up scenarios...
BCI devices used as passive sensors represent a frontier for monitoring people and to know their inner states. In the automotive domain, driver systems look at such technologies monitor greater level of details both cognitive emotional states drivers, aim understanding driving conditions react timely in case they are judged dangerous from safety perspective. This study aims if brain imaging sensors, less invasive forms, could be accepted by sake an increased while driving. To this purpose,...
Purpose: This study examines patients' perspectives on the integration of artificial intelligence (AI) in radiology through focus groups, aiming to identify main issues and areas for improvement. It is part a larger research project that employs various methodologies explore views both patients radiologists regarding AI tools. Methods: We conducted two groups using narrative story vignettes: one with who self-assessed as experts other non-AI experts. Results: The revealed diverse opinions...
This thesis has been carried out in the field of Computer Networks. We have looked after two challenging and popular multimedia applications over Internet, namely Real-time Multimedia Applications, considering Conferencing Voice IP (VoIP) services general, and Content-Oriented that are web such as User Generated Contents (UGC) platforms Online Social conducted our studies starting from a thorough review both functional non-functional issues related to above mentioned application families. We...
Leveraging the driver state classification performed by state-of-the-art intelligent monitoring systems, new multimodal Human Machine Interfaces (HMIs) strategies can be designed to support safe driving. With purpose of engaging drivers in driving behaviors keeping them aware their state, visual nudges, voice interaction, ambient lights, and music have been exploited design an HMI prototype that kind. This study presents results a focus group with daily assess proposed approach terms its...
Driver monitoring systems (DMS) have been developed to improve road safety by collecting data on driver status and behavior profile their ability drive safely. Nowadays, DMSs aim monitor different types of drivers' emotions distractions, allowing for the design intelligent support that are aware state. To this purpose, they require carefully designed training datasets supervised learning algorithms ensure state detection reliability. In paper we present an experimental procedure collect kind...