A5082933570- Human Mobility and Location-Based Analysis
- Privacy-Preserving Technologies in Data
- Privacy, Security, and Data Protection
- COVID-19 Digital Contact Tracing
- Data Management and Algorithms
- Artificial Intelligence in Healthcare and Education
- Vehicular Ad Hoc Networks (VANETs)
- Traffic Prediction and Management Techniques
- Ethics and Social Impacts of AI
- Data-Driven Disease Surveillance
- Technology Adoption and User Behaviour
- Blockchain Technology Applications and Security
- Data Quality and Management
- Explainable Artificial Intelligence (XAI)
- Mobile Health and mHealth Applications
- Adversarial Robustness in Machine Learning
- Organizational and Employee Performance
- Data Mining Algorithms and Applications
- Sepsis Diagnosis and Treatment
- Heart Failure Treatment and Management
- Transportation and Mobility Innovations
- Geographic Information Systems Studies
- User Authentication and Security Systems
- Data Visualization and Analytics
- Transportation Planning and Optimization
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo"
2014-2025
National Research Council
2021-2024
University of Pisa
2013-2021
Azienda Ospedaliera Universitaria Pisana
2018
Abstract How can big data help to understand the migration phenomenon? In this paper, we try answer question through an analysis of various phases migration, comparing traditional and novel sources models at each phase. We concentrate on three phase describing state art recent developments ideas. The first includes journey , study flows stocks, providing examples where have impact. second discusses stay i.e. migrant integration in destination country. explore sets that be used quantify...
The rapid dynamics of COVID-19 calls for quick and effective tracking virus transmission chains early detection outbreaks, especially in the "phase 2" pandemic, when lockdown other restriction measures are progressively withdrawn, order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps being proposed large scale adoption by many countries. A centralized approach, where data sensed app all sent a nation-wide server, raises concerns about citizens' privacy...
Privacy is ever-growing concern in our society and becoming a fundamental aspect to take into account when one wants use, publish analyze data involving human personal sensitive information. Unfortunately, it increasingly hard transform the way that protects information: we live era of big characterized by unprecedented opportunities sense, store social describing activities great detail resolution. As result, privacy preservation simply cannot be accomplished de-identification alone. In...
Human mobility data are an important proxy to understand human dynamics, develop analytical services, and design mathematical models for simulation what-if analysis. Unfortunately very sensitive since they may enable the re-identification of individuals in a database. Existing frameworks privacy risk assessment provide providers with tools control mitigate risks, but suffer two main shortcomings: (i) have high computational complexity; (ii) must be recomputed every time new records become...
This article's main contributions are twofold: 1) to demonstrate how apply the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI in practice domain of healthcare and 2) investigate research question what does "trustworthy AI" mean at time COVID-19 pandemic. To this end, we present results a post-hoc self-assessment evaluate trustworthiness an system predicting multiregional score conveying degree lung compromise patients, developed verified by...
Abstract The exponential increase in the availability of large-scale mobility data has fueled vision smart cities that will transform our lives. truth is we have just scratched surface research challenges should be tackled order to make this a reality. Consequently, there an increasing interest among different communities (ranging from civil engineering computer science) and industrial stakeholders building knowledge discovery pipelines over such sources. At same time, widespread also raises...
Abstract The objective of this research is to investigate how cultural differences affect consumers’ online purchase behavior. We reviewed the recent literature on cross-cultural studies behavior and building Hofstede’s theory dimensions planned (TPB), we developed a conceptual model exploring national culture influence perceptions website usability, trust, perceived risk, which in turn impact intention use A web-based questionnaire was distributed sample 350 European Asian consumers...
In patients with septic shock, the presence of an elevated heart rate (HR) after fluid resuscitation marks a subgroup particularly poor prognosis. Several studies have shown that HR control in this population is safe and can potentially improve outcomes. However, all were conducted single-center setting. The aim multicenter study to demonstrate administration highly beta1-selective ultrashort-acting beta blocker landiolol shock persistent tachycardia (HR ≥ 95 beats per minute [bpm])...
Abstract This paper presents a framework for research infrastructures enabling ethically sensitive and legally compliant data science in Europe. Our goal is to describe how design implement an open platform big social science, including, particular, personal data. To this end, we discuss number of infrastructural, organizational methodological principles be developed concrete implementation. These include not only systematically tools methodologies that effectively enable both the empirical...
Abstract Today, many users are actively using Twitter to express their opinions and share information. Thanks the availability of data, researchers have studied behaviours social networks these users. International migration studies also benefited from this media platform improve statistics. Although diverse types been so far on Twitter, migrants natives not before. This paper aims fill gap by studying characteristics Twitter. To do so, we perform a general assessment features including...
Currently, privacy risks assessment is mainly performed as audits conducted by data analysts. In the TAILOR project, we promote a more systematic and automatic approach based on interpretable metrics formal methods to evaluate control tension between utility. this paper, focus raised publishing time series datasets, survey developed in analyze quantify depending different publisher attacker models.