Abstract
Cognitive theorists believe that the learning process involves the integration of events into actives organizational structures termed schemata. Schemata serve a number of functions in human cognition: schemata regulates attention, organizes searches of the environment and “fill the gaps” during information processing. Thus, the mind uses schemata to selectively organize and processes all the information individuals receive from the world. This perspective fits e.g. in teaching blind and deaf people alongside of children with special education needs. The aim of the research developed until the moment was to prove that the full integration of the concept of teaching and learning in the light of cognitive theories. © Springer International Publishing AG 2018.

Abstract
As life expectancy grows and the population requirements for satisfactory health and wellness levels increases, there is a clear opportunity for the incorporation of alternative techniques and tools for promoting health and preventing disease. One of these tools, is the use of thermal water-based treatments, commonly known as thermalism, as tools to trigger patients’ overall wellness. Despite the collective assumption of the effects of thermalism, there is little to no scientific evidence of these treatments, thus impairing the potential of this activity to become more widespread in society. Thus, with this paper, we present a conceptual model for a non-invasive sensing system based on wearables that can monitor a set of patients’ biomarkers which will serve as the basis for the validation of the effects of thermalism. This system will also serve as a management and operation control tool for thermal SPA managers and technical directors. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Considering the growing volume of information and services available on the web, it has become essential to provide websites and applications with tools, such as recommender systems, capable of helping users to obtain the information and services appropriate to their interests. Due to the complexity of web adaptation and the ability of multi-agent systems to deal with complex problems, the use of multi-agent approaches in recommender systems has been increasing. In the present work, we make a thorough review of the use of multi-agent-based recommender systems. The review shows the diversity of applications of multi-agent systems in recommender systems, namely on what concerns the diversity of domains, different types of approaches and contribution to the performance improvement of the recommender systems.

Abstract
Guiding the building occupants under fire emergency to a safe place is an open research problem. Finding solutions to address the problem requires a perfect knowledge of the fire building evacuation domain. The use of ontologies to model knowledge of a domain allows a common and shared understanding of that domain, between people and heterogeneous systems. This paper presents an ontology that aims to build a knowledge model to better understand the referred domain and to help develop more capable building evacuation solutions and systems. The herein proposed ontology considers the different variables and actors involved in the fire building evacuation process. We followed the Methontology methodology for its developing, and we present all the development steps, from the specification to its implementation with the Protégé tool.

Abstract
In the areas of machine-learning/big data, feature selection is normally regarded as a very important problem to be solved, as it directly impacts both data analysis and model creation. The problem of optimizing the selected features of a given dataset is not always trivial, however, throughout the years various ways to counter this optimization problem have been presented. This work presents how feature-selection fits in the larger context of multi-objective problems as well as a review of how both multi-objective evolutionary algorithms and metaheuristics are being used in order to solve feature selection problems.

Abstract
The daily stress we, as population, are subjected has negative impacts on physical and mental health, making people age faster. With the increase in life expectancy, the population started to search for ways to ensure they reach the older ages with a healthier and better lifestyle, resulting in an increase of interest and demand for thermalism and wellness tourism. Although thermalism is recognized to have several benefits with regard to the combat and prevention of certain pathologies, this has not yet been fully proven. So, in this paper, we presented a sensing system, capable of not only recording thermalist's biometric data, but also getting the data ready and prepared to be processed by any analytic tool with the aim of showing the impact that this sector has on the health of its practitioners.