Appropriate teaching–learning strategies lead to student engagement during learning activities. Scientific progress and modern technology have made it possible to measure engagement in educational settings by reading and analyzing student physiological signals through sensors attached to wearables. This work is a review of current student engagement detection initiatives in the educational domain. The review highlights existing commercial and non-commercial wearables for student engagement monitoring and identifies key physiological signals involved in engagement detection. Our findings reveal that common physiological signals used to measure student engagement include heart rate, skin temperature, respiratory rate, oxygen saturation, blood pressure, and electrocardiogram (ECG) data. Similarly, stress and surprise are key features of student engagement.

Breast cancer is one of the leading causes of death among women worldwide. There are a number of techniques used for diagnosing this disease: mammography, ultrasound, and biopsy, among others. Each of these has well-known advantages and disadvantages. A relatively new method, based on the temperature a tumor may produce, has recently been explored: thermography. In this paper, we will evaluate the diagnostic power of thermography in breast cancer using Bayesian network classifiers. We will show how the information provided by the thermal image can be used in order to characterize patients suspected of having cancer. Our main contribution is the proposal of a score, based on the aforementioned information, that could help distinguish sick patients from healthy ones. Our main results suggest the potential of this technique in such a goal but also show its main limitations that have to be overcome to consider it as an effective diagnosis complementary tool.

This paper introduces SagaMAS: a Multi-Agent based framework on development, dealing with distributed transactions in the microservices architecture. Microservices are an architectural style where the distributed system is decomposed in a series of highly cohesive and independent services. Each microservice can have different implementations and data persistence technologies, resulting in heterogeneous distributed systems. Given its heterogeneity and distributed nature, an open challenge in this architecture is the proper management of distributed transactions that expand through several microservices. Multi-Agent Systems are by definition distributed systems suited for complex coordination tasks, such as this. The proposed framework can be seen as a decoupled autonomous layer that coordinates the distributed transactions of the system, relieving the microservice developer from such tasks, and simplifying microservice interactions. Unlike existing approaches, our proposal is conceived and usable at an abstraction level appropriate to express reliability and robustness issues in terms of agent coordination.