| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNISA990005633010203316 |
|
|
Autore |
BUYENS, Jim |
|
|
Titolo |
Usare Microsoft FrontPage oltre ogni limite : versione 2002 / Jim Buyens |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
[Segrate] : Mondadori Informatica, 2001 |
|
|
|
|
|
|
|
Descrizione fisica |
|
XXXII, 959 p. ; 24 cm + 1 CD-ROM |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Programmi per elaboratori - Microsoft front page. 2002 - Manuali |
|
|
|
|
|
|
Collocazione |
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Note generali |
|
|
|
|
|
|
2. |
Record Nr. |
UNINA9910592987103321 |
|
|
Titolo |
Disease Control Through Social Network Surveillance / / edited by Thirimachos Bourlai, Panagiotis Karampelas, Reda Alhajj |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
|
|
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
|
|
Edizione |
[1st ed. 2022.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (237 pages) |
|
|
|
|
|
|
Collana |
|
Lecture Notes in Social Networks, , 2190-5436 |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
|
|
Soggetti |
|
Artificial intelligence - Data processing |
Medical informatics |
Public health |
Epidemiology |
Data Science |
Health Informatics |
Public Health |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di bibliografia |
|
Includes bibliographical references and index. |
|
|
|
|
|
|
Nota di contenuto |
|
Chapter 1. Analysis of public perceptions towards the COVID-19 vaccination drive: A case study of Tweets with Machine Learning classifiers (Kaushal Kumar) -- Chapter 2. Spreader-centric Fake News Mitigation framework based on Epidemiology (Bhavtosh Rath) -- Chapter 3. Understanding How Readers Determine the Legitimacy of Online Medical News Articles in the Era of Fake News (Srihaasa Pidikiti) -- Chapter 4. Trends, Politics, Sentiments, and Misinformation: Understanding People’s Reactions to COVID-19 During its Early Stages (Omar Abdel) -- Chapter 5. Citation Graph Analysis and Alignment between Citation Adjacency and Themes or Topics of Publications in the Area of Disease Control through Social Network Surveillance (Moses Boudourides) -- Chapter 6. Privacy in Online Social Networks: A Systematic Mapping Study and a Classification Framework (Sarah Bouraga) -- Chapter 7. Beyond Influence Maximization: Volume Maximization in Social Networks (Abhinav Choudhury) -- Chapter 8. Concerns of IndianPopulation on Covid-19 Vaccine Shortage amidst second wave infection rate spikes: A Social Media Opinion Analysis (Remya Lathabhavan) -- Chapter 9. Effects of Face Masks on the performance of Modern Face Detectors (Victor Philippe) -- Chapter 10. Multispectral Face Mask Compliance Classification During a Pandemic (Jacob Rose) -- Chapter 11. On the Effectiveness of Periocular-Based Human Authentication when Wearing Face Masks to Slow the Spread of COVID-19 (Ananya Zabin). |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
This book examines modern paradigms of disease control based on social network surveillance applications, including electronic sentinel surveillance and wireless application-based surveillance science. It also highlights topics that integrate statistical and epidemiological sciences with surveillance practice and, in order to reflect the evolution of social networking practices, discusses topics concerning the challenges for surveillance theory and practice. In turn, the book goes a step further by providing insights on how we need to analyse epidemiological trends by following best practices on distinguishing useful information from noise, namely fake news, false reporting of disease incidents and events, etc. At the same time, we need to be able to protect health-focused applications and communication tools via cybersecurity technologies and to ensure that anonymity of reporting and privacy are preserved. In closing, the book discusses the role and impact of social media on disease surveillance, as well as the current role of communities in infectious disease surveillance and control. |
|
|
|
|
|
|
|
| |