A proposal of a classification model for the cognitive workload of human activity in a context-aware system

The skill level of a person in processing information, reacting to his/her surroundings and decision making for performing an activity is determined by the allocation of the mental resources demanded by such activity. When the allocation is inappropriate, there is a higher possibility for some accident to occur. Thus, one can notice that the cognitive workload spent by the person is an important variable that can take him to a risky situation. Since it is not possible to measure the cognitive workload spent by a person during the performance of an activity directly, we noticed the need to evaluate the level of his/her performance in order to be possible to infer the cognitive workload used. So, we propose the creation of a model to classify the cognitive workload based on the behavioral model skill-rule-knowledge and the relations of performance properties with the context surrounding the person. The evaluation of the model was made using a public dataset and the results showed a promising approach for the classification of human performances.Keywords: human activity, context-aware middleware, ubiquity, cognitive workload, human performance

A context-aware model for human activity prediction and risk inference in actions

Even though human activities may result in injuries, there is not much discussion in the academy of how ubiquitous computing could assess such risks. So, this paper proposes a model for the Activity Manager layer of the Activity Project, which aims to predict and infer risks in activities. The model uses the Activity Theory for the composition and prediction of activities. It also infers the risk in actions based on changes in the user’s physiological context caused by the actions, and such changes are modeled according to the Hyperspace Analogue to Context model. Tests were conducted and the developed models outperformed proposals found for action prediction, with an accuracy of 78.69%, as well as for risk situation detection, with an accuracy of 98.94%, showing the efficiency of the proposed solution.Keywords: activities of daily living, Activity Theory, activity recognition, activity prediction, risk in actions

UM SISTEMA DE GERENCIAMENTO ACADÊMICO GEOGRAFICAMENTE DISTRIBUÍDO COM SUPORTE A UM ÚNICO PONTO DE AUTENTICAÇÃO doi: http://dx.doi.org/10.5892/RUVRV.91.211219

Este artigo apresenta uma proposta para autenticação em aplicação pertencentes a domínios distintos, através de um único ponto de acesso. A solução está sendo implementada para um sistema open-source de gerenciamento acadêmico (SIGA-EPCT). No contexto deste projeto, com uso do Shibboleth e do SAML, será possível racionalizar os recursos oferecidos pelos Institutos Federais, Integrar os diferentes módulos do SIGA-EPCT e compartilhar a base de dados com o Ministério da Educação

Um sistema de gerenciamento acadêmico geograficamente distribuído com suporte a um único ponto de autenticação

This paper presents a proposal for application's authenticaton, allowing different domains to authenticate in a single access point. This solution is being implemented into an peon-source Academic Management System called SIGA-EPCT. By using Shibboleth and SAML, it will be possible to share computational resources between Federal Institutes, integrating the different modules of SIGA-EPCT and, also, share information with the Ministry of Education.Este artigo apresenta uma proposta para autenticação em aplicação pertencentes a domínios distintos, através de um único ponto de acesso. A solução está sendo implementada para um sistema open-source de gerenciamento acadêmico (SIGA-EPCT). No contexto deste projeto, com uso do Shibboleth e do SAML, será possível racionalizar os recursos oferecidos pelos Institutos Federais, Integrar os diferentes módulos do SIGA-EPCT e compartilhar a base de dados com o Ministério da Educação