Article
Automation & Control Systems
Xiang Li, Hai Wang, Zeshui Xu
Summary: The study proposes a novel three-way decision method for making decisions on whether enterprises should resume work post-epidemic. The method involves describing enterprise attributes, calculating attribute weights using the entropy weight method, and ultimately making decision results based on minimizing losses.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2021)
Article
Environmental Sciences
Murgante Beniamino, Balletto Ginevra, Borruso Giuseppe, Saganeiti Lucia, Pilogallo Angela, Scorza Francesco, Castiglia Paolo, Arghittu Antonella, Dettori Marco
Summary: This study uses the spatial analytical hierarchy process method to analyze the impact of environmental, climatic, and land management factors on the COVID-19 pandemic in Italy and develop three different hazard scenarios. The results show disparities in the distribution of hazard areas in Italy, with environmental factors playing a crucial role. These findings provide decision makers with guidance for policy choices based on different priorities.
ENVIRONMENTAL RESEARCH
(2022)
Article
Biology
Pietro M. Boselli, Jose M. Soriano
Summary: Every epidemic brings health, economic, social, and environmental problems that need to be addressed promptly. This study uses a mathematical model to analyze the trends of infected and deceased individuals, aiming to predict the duration and phases of the epidemic. The analysis of cumulative deaths provides more accurate forecasts of the epidemic's development.
Article
Immunology
Michela Sabbatucci, Anna Odone, Carlo Signorelli, Andrea Siddu, Andrea Silenzi, Francesco Paolo Maraglino, Giovanni Rezza
Summary: The COVID-19 pandemic has had a significant impact on the Italian National Health System, leading to decreased routine childhood vaccine coverage rates. However, there has been an increase in chicken pox vaccination while recommended vaccinations have been moderately affected. Effective communication campaigns and educational programs are crucial to reinforce vaccination confidence and behavior during and beyond the COVID-19 era.
Article
Computer Science, Artificial Intelligence
James M. Tien
Summary: This paper focuses on COVID-19, a respiratory epidemic or infection that started in December 2019 and has affected most, if not all, of the world's 253 countries. It provides an intermediary account of the continuing pandemic and explores the infection's three phases: epidemic, pandemic, and endemic. The lessons learned from the COVID-19 phases should help in better preparation for future pathogens and deadly diseases.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2023)
Article
Multidisciplinary Sciences
Anne-Maria Schweizer, Anna Leiderer, Veronika Mitterwallner, Anna Walentowitz, Gregor Hans Mathes, Manuel Jonas Steinbauer
Summary: During the COVID-19 pandemic, there was a clear increase in outdoor cycling activities in urban public green spaces in Germany, while there was no significant change in cycling activities in rural areas. Fitness app data can be used to monitor visitor behavior and frequency, highlighting the importance of accessible green spaces for maintaining physical fitness and health, especially during times of crisis.
Article
Biology
Christophe Besse, Gregory Faye
Summary: The study introduces a new model that describes the dynamics of epidemic spreading on connected graphs, using a PDE-ODE system. It shows that the model is effective in capturing the characteristics of epidemic spreading and proposes a numerical scheme for validation and simulation.
JOURNAL OF MATHEMATICAL BIOLOGY
(2021)
Article
Multidisciplinary Sciences
Maira Aguiar, Joseba Bidaurrazaga Van-Dierdonck, Javier Mar, Nicole Cusimano, Damian Knopoff, Vizda Anam, Nico Stollenwerk
Summary: As the COVID-19 pandemic evolves, research on mathematical modeling plays a crucial role in understanding the epidemiological dynamics of disease spreading and guiding public health interventions. Analyzing critical fluctuations around the epidemiological threshold can help explain the dynamic behavior of COVID-19 even when the community disease transmission rate remains relatively constant.
SCIENTIFIC REPORTS
(2021)
Article
Mathematical & Computational Biology
Roman Zuniga Macias, Humberto Gutierrez-Pulido, Edgar Alejandro Guerrero Arroyo, Abel Palafox Gonzalez
Summary: This study proposes a method for dividing a territory into time-varying epidemic regions and establishing a novel Lagrangian-SEIR model to describe the dynamics of the epidemic. Taking the COVID-19 epidemic in Jalisco state, Mexico as an example, the ability of this method to identify local outbreaks and reproduce the epidemic curve is discussed. The results of the study show that the method has a Relative Root Mean Squared Error (RRMSE) below 15% in most regions and below 5% at the state level.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2022)
Article
Chemistry, Physical
Andreas Drexler, Liese Vandewalle, Tom Depover, Kim Verbeken, Josef Domitner
Summary: The importance of verifying the evaluation procedures according to Kissinger's theory for multiple types of hydrogen trapping sites in advanced high-strength steels (AHSS) is highlighted by simulating theoretical TDS spectra and comparing them with experimental results. It is strongly recommended to apply the Kissinger theory only for the evaluation of single or well separated TDS peaks, with complementary microstructural variation and characterization needed for overlapping peaks.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2021)
Article
Multidisciplinary Sciences
Subrata Paul, Animesh Mahata, Supriya S. Mukherjee, Prakash Chandra Mali, Banamali Roy
Summary: This manuscript explores the fractional order SEIQRD compartmental model of COVID-19 with six different categories using the Caputo approach. Several findings have been established regarding the existence and uniqueness criterion, non-negativity, and boundedness of the solution for the new model. The study aims to investigate the COVID-19 transmission dynamics in Italy and analyzes the effects of wearing face masks on reducing the propagation of the disease.
Article
Computer Science, Artificial Intelligence
Xiang Li, Hai Wang, Zeshui Xu
Summary: The outbreak of epidemic has greatly affected China's investment market, making it challenging for enterprises to judge the prospects of investment projects and make the right decisions. This study proposes a novel three-way decision model to select investment projects by describing project attributes, determining weights, calculating similarity measures, and setting threshold parameters.
FUZZY OPTIMIZATION AND DECISION MAKING
(2023)
Article
Mathematics, Applied
Giulia Bertaglia, Lorenzo Pareschi
Summary: This paper addresses the importance of spatial networks in epidemic spread and the uncertainty in data-driven models when dealing with infectious diseases. By using a hyperbolic compartmental model on networks, it accurately describes the spread of COVID-19 in Italy and the Lombardy Region.
MATHEMATICAL MODELS & METHODS IN APPLIED SCIENCES
(2021)
Article
Biology
Ronald Manriquez, Camilo Guerrero-Nancuante, Carla Taramasco
Summary: Our study evaluates protection strategies through infectious disease modeling with COVID-19 data, indicating that the model provides important protection for the population by recognizing super-propagating individuals, which is crucial in combating COVID-19. The effectiveness of immunizing nodes in a network using the DIL-W-alpha ranking is assessed, emphasizing the key role of immunization in stopping disease spread.
Article
Public, Environmental & Occupational Health
Giovanni Ortosecco, Orazio Vaia
Summary: COVID-19 is a multi-organ pathological disease that severely affects the respiratory system, especially causing respiratory failure in the lungs. Elderly patients with comorbidities are at higher risk of rapid deterioration. The implementation of restrictive measures from March 10th in Italy has shown to be effective in controlling the epidemic.
JOURNAL OF EPIDEMIOLOGY AND GLOBAL HEALTH
(2021)
Article
Computer Science, Artificial Intelligence
Giuseppe D'Aniello, Angelo Gaeta, Matteo Gaeta, Stefania Tomasiello
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2018)
Article
Automation & Control Systems
Hamido Fujita, Angelo Gaeta, Vincenzo Loia, Francesco Orciuoli
IEEE TRANSACTIONS ON CYBERNETICS
(2019)
Article
Computer Science, Artificial Intelligence
Hamido Fujita, Angelo Gaeta, Vincenzo Loia, Francesco Orciuoli
APPLIED INTELLIGENCE
(2019)
Article
Computer Science, Artificial Intelligence
Hamido Fujita, Angelo Gaeta, Vincenzo Loia, Francesco Orciuoli
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2020)
Article
Computer Science, Artificial Intelligence
Angelo Gaeta, Vincenzo Loia, Francesco Orciuoli
Summary: This paper presents a comprehensive model for representing and reasoning on situations to support decision makers in Intelligence analysis activities. The model represents operational situations according to three perspectives and is based on principles and methods of Granular Computing.
APPLIED INTELLIGENCE
(2021)
Article
Computer Science, Artificial Intelligence
Angelo Gaeta, Francesco Orciuoli, Mimmo Parente
Summary: The virtual counselling system is designed to improve user awareness of emotional situations in computer-mediated communication and provide informed recommendations to users involved in a conversation. The system utilizes emotional signatures of individuals and groups, along with three-way decisions, to classify recognized situations based on emotional contagion dynamics. Experimental results from a collaboration between university students show promising outcomes in terms of system accuracy.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2021)
Article
Computer Science, Information Systems
Roberto Abbruzzese, Angelo Gaeta, Vincenzo Loia, Luigi Lomasto, Francesco Orciuoli
Summary: The work proposes a new method to detect influential news in online communities by applying the Three-Way Decisions approach based on Probabilistic Rough Sets to categorize online users into three parts. It then maps these parts onto a structure called Hexagons of Opposition to reason about the impact of news on opinions of specific communities over time, introducing two indicators to measure the impact of news. The method has been experimented on real data and discussed with promising results.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Angelo Gaeta, Vincenzo Loia, Luigi Lomasto, Francesco Orciuoli
Summary: The paper presents and evaluates an approach based on Rough Set Theory to analyze Information Disorder phenomena. Rough Set Theory concepts and constructs are used to model and reason on social media user groups and sets of information. Information theoretic measures are used to evaluate Complexity and Milestone concepts in Information Disorder. The adoption of Rough Set Theory constructs and operators in this new field allows for modeling and reasoning on key elements of Information Disorder and interpreting its effects.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Angelo Gaeta
Summary: The paper proposes using set-theoretic measures to define and adopt structures of opposition and evaluate emotional dynamics in conversations on social media. A graded hexagon of opposition is used to compare emotional profiles, with set-theoretic measures constructing the hexagon and analyzing the conversation's tendency towards empathy or lack thereof. These results are important for social media providers to receive early warnings about emotional dynamics that may lead to information disorder, and have been evaluated using conversations from the Empathetic Dialogue dataset.
Article
Education & Educational Research
Maiga Chang, Marta De Angelis, Angelo Gaeta, Francesco Orciuoli, Mimmo Parente
Summary: This paper presents the results of the Inf@nziaDigiTales3.6 project, which focuses on the design, development, and evaluation of an augmented reality application for situated learning experiences in a smart city. The application, designed for primary school children, aims to help them understand the geometric shapes and colors associated with road signs in a city. The evaluation results confirm the benefits of augmented reality and mobile technologies in terms of engagement, enjoyment, and willingness to repeat the experience. The use of augmented reality and the intelligent tutoring system has also influenced the memorization processes of figures, colors, and signal contents.
INTERACTIVE LEARNING ENVIRONMENTS
(2023)
Article
Computer Science, Artificial Intelligence
Angelo Gaeta, Vincenzo Loia, Francesco Orciuoli, Mimmo Parente
Summary: This paper proposes a method that combines time-based granulation and three-way decisions to help decision makers understand and reason on learned granular structures conceptualizing spatio-temporal events. Formal concept analysis is used as a central tool in guiding time-based granulation and supporting reasoning and decision-making processes. The method is effective and simple, with an illustrative example and evaluation on a real dataset of forest fires showcasing its application in supporting decision-making in environmental monitoring issues.
GRANULAR COMPUTING
(2021)
Article
Education & Educational Research
Marta De Angelis, Angelo Gaeta, Francesco Orciuoli, Mimmo Parente
JOURNAL OF E-LEARNING AND KNOWLEDGE SOCIETY
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Angelo Gaeta, Vincenzo Loia, Francesco Orciuoli
FUZZY LOGIC AND SOFT COMPUTING APPLICATIONS, WILF 2016
(2017)
Article
Computer Science, Artificial Intelligence
Giuseppe D'Aniello, Angelo Gaeta, Vincenzo Loia, Francesco Orciuoli
GRANULAR COMPUTING
(2017)