IJIMAI 2020 - Regular Issue - Vol. 6 Issue 4

The present regular issue consists of 10 works with a great variety of topics. It begins with two interesting health-related works: the first one, reviews different approaches that can help fight COVID-19 and the second one, tries to solve an optimal control problem of cancer treatment using an artificial neural network. It continues with algorithms that can help in industrial processes such as reducing the temperature of electronic circuits or carrying out chromium layer thickness forecast. Radically changing the subject, the next paper proposes a method to identify the most influential nodes in social networks that can be the source of rumor spreading. Another different work focuses on how to interact with virtual 3D environments in a cheap way by using multiple embedded markers in a specialized manner. In this issue, a work has also been carried out to improve the identification of polysemy in natural language processing tasks. The following two works are related to assess students satisfaction: on the perception of students when they are evaluated by an artificial intelligence and not by a human, and on the quality of the learning content and the methodology at unit level for any course and at any time. Finally, the issue closes with a paper in which a tool can classify the emotions of users based only on non-invasive techniques like their keyboard typing and mouse usage pattern.
As a novelty, we are pleased to announce that this is the first regular issue in IJIMAI that contains a special section with a collection of works on a specific topic. In this case, the section is presented under the title "Artificial Intelligence and Sensor Informatics: Exploring Smart City and Construction Business Implications” and is edited by Prof. Shaofei Wu from the Wuhan Institute of Technology (China). The section includes 7 exciting works which topics range from industrial robots to energy estimation based on machine learning algorithms.