Analysis of a Sorter Cascade Applied to Control a Wheelchair

The precise eye state detection is a fundamental stage for various activities that require human-machine interaction (HMI). This chapter presents an analysis of the implementation of a system for navigating a wheelchair with automation (CRA), based on facial expressions, especially eyes closed using a Haar cascade classifier (HCC). Aimed at people with locomotor disability of the upper and lower limbs, the state detection was based on two steps: the capture of the image, which concentrates on the detection actions and image optimization; actions of the chair, which interprets the data capture and sends the action to the chair. The results showed that the model has excellent accuracy in identification with robust performance in recognizing eyes closed, bypassing well occlusion issues and lighting with about 98% accuracy. The application of the model in the simulations opens the implementation and marriage opportunity with the chair sensor universe aiming a safe and efficient navigation to the user

Utilização da simulação computacional na verificação da cooperação de uma população em um ambiente simulado = Use of computer simulation to verify the cooperation of a population in a simulated environment

En el presente artículo realizamos un análisisde comportamientos de cooperación enambiente simulado. El presente estudio tienecomo finalidad observar los resultados de la interacciónde los caracteres egoísta, vengativo yaltruista en constante interacción a lo largo degeneraciones. Durante el proceso se desarrollaronalgoritmos que emulan una de las aplicacionesde la teoría de los juegos, el dilemadel prisionero y otro que utiliza la forma en quelos autómatas móviles se mueven-sedientosde una malla virtual. La contribución que conseguimoses dar un valor porcentual máximo auna población aceptada con carácter egoísta yverificar que los caracteres vengativo y altruistatienen un tiempo de vida muy próximo