A NOTE ON CONDITIONAL IMPLICATION

It is well known that there exists a tight connection between nonmonotonic reasoning and conditional implication. Many researchers have investigated it from various angles. Among th em, C.Boutilier and P.Lamarre have shown that some conditional implication may b e regarded as the homology of different nonmonotonic consequence relations. In t his paper, based on the plausibility space introduced by Friedman and Halpern, w e characterize the condition logic in which conditional implication is nonmonoto nic, and this result characterizes the conditional implication which may be rega rded as the corresponding object in Meta language for nonmonotonic inference rel ations.

MEDICLOUD:a holistic study on the digital evolution of medical data

The Corona Virus Disease 2019(COVID-19) pandemic has taught us many valuable lessons regarding the importance of our physical and mental health. Even with so many technological advancements, we still lag in developing a system that can fully digitalize the medical data of each individual and make it readily accessible for both the patient and health worker at any point in time. Moreover, there are also no ways for the government to identify the legitimacy of a particular clinic. This study merges modern technology with traditional approaches,thereby highlighting a scenario where artificial intelligence(AI) merges with traditional Chinese medicine(TCM), proposing a way to advance the conventional approaches. The main objective of our research is to provide a one-stop platform for the government, doctors,nurses, and patients to access their data effortlessly. The proposed portal will also check the doctors’ authenticity. Data is one of the most critical assets of an organization, so a breach of data can risk users’ lives. Data security is of primary importance and must be prioritized. The proposed methodology is based on cloud computing technology which assures the security of the data and avoids any kind of breach. The study also accounts for the difficulties encountered in creating such an infrastructure in the cloud and overcomes the hurdles faced during the project, keeping enough room for possible future innovations. To summarize, this study focuses on the digitalization of medical data and suggests some possible ways to achieve it. Moreover, it also focuses on some related aspects like security and potential digitalization difficulties.

Analysis on the differences in the development of basic researchers in the field of Al in China

Artificial intelligence(AI)is an important driving force in the new round of scientific and technological revolution and industrial transformation,China must grasp the opportunity to its development.Basic researcher's ability was the inexhaustible driving force to promote the long-term development of AI.The paper focused on 2763 AI researchers who engaged in basic research.The paper analyzed the differences in city distribution and research direction of this group in China,and further explored the influence of different cities on research output,as well as the interactive influence between city and institution on their research output.The study found that there was a prominent phenomenon of aggregation of AI basic researchers in China,and their research fields were mainly focused on machine learning,computer vision,patterm recognition and data mining.The economic level of the city had a positive impact on the paper output and the project undertaken by researchers.The development vitality of the city had a positive impact on the researchers'patent output.The high-quality platform of the institution would make up for the disadvantages caused by the city's lower economy.Therefore,in China,it was necessary to determine the development orientation of cities at different levels so that they could play different roles in the industrial development.Economically underdeveloped cities should allocate resources rationally,enhance the deep cooperation between non-first-class institutions and local AI enterprises,and provide a good scientific research ecological environment for the growth of local AI basic researchers.