Artificial intelligence for Novel Corona Virus (COVID-19) Pandemic

COVID-19 outbreak has created havoc around the world and has brought life to a disturbing halt claiming thousands of lives worldwide and infected cases rising every day. With technological advancements in Artificial Intelligence (AI), AI-based platforms can be used to deal with COVID-19 pandemic and accelerate the processes ranging from crowd surveillance to medical diagnosis. This paper renders a response to battle the virus through various AI techniques by making use of its subsets such as Machine Learning (ML), Deep learning (DL) and Natural Language Processing (NLP). A survey of promising AI methods which could be used in various applications to facilitate the processes in this pandemic along potential of AI and challenges imposed are discussed thoroughly. This paper relies on the findings of the most recent research publications and journals on COVID-19 and suggests numerous relevant strategies. A case study on the impact of COVID-19 in various economic sectors is also discussed. The potential research challenges and future directions are also presented in the paper.

Privacy and Confidentiality in Process Mining: Threats and Research Challenges

Privacy and confidentiality are very important prerequisites for applying process mining to comply with regulations and keep company secrets. This article provides a foundation for future research on privacy-preserving and confidential process mining techniques. Main threats are identified and related to a motivation application scenario in a hospital context as well as to the current body of work on privacy and confidentiality in process mining. A newly developed conceptual model structures the discussion that existing techniques leave room for improvement. This results in a number of important research challenges that should be addressed by future process mining research.

Delphi MIX for the Construction of Future Critical Scenarios in Social Distancing

In the era of digital society, social research must devise innovative and adaptive methodologies in relation to new forms of communication and social interaction. The social distancing measures aimed at containing the spread of COVID-19 have produced the need for social sciences to face new research challenges by making the best possible use of information technology and tools. The researchers' aim is to present an innovative method of remote participatory social research, which can be framed in the context of future studies. This method, called Delphi MIX, has been developed by CNR-Irpps researchers since 2003, and its last adjustment has been designed as a consequence of the coronavirus crisis. Delphi MIX is a method for participatory strategic planning. It can be understood as a political agenda that aims to a desirable and achievable future.