2006
Autores
Conceição, AS; Moreira, AP; Costa, PJ;
Publicação
ICINCO 2006, Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics, Robotics and Automation, Setúbal, Portugal, August 1-5, 2006
Abstract
2009
Autores
Neto, P; Pires, JN; Moreira, AP;
Publicação
18th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2009, Toyama International Conference Center, Japan, September 27 - October 2, 2009
Abstract
2010
Autores
Neto, P; Mendes, N; Pires, JN; Moreira, AP;
Publicação
IEEE Conference on Automation Science and Engineering, CASE 2010, Toronto, ON, Canada, 21-24 August, 2010
Abstract
1999
Autores
Gomes, MC; Gomes, JJ; Paulo, AC;
Publicação
EUROPEAN JOURNAL OF EPIDEMIOLOGY
Abstract
Techniques of time series analysis were used to examine historical records of the incidence of diphtheria, pertussis, and measles, and of deaths by measles in Portugal during the twentieth century. There are statistically significant seasonal and long-term oscillations in the incidence of these diseases. Seasonal oscillations appear to be in close association with the resumption of school classes in the fall in the case of diphtheria, but not in pertussis and measles. Long-term oscillations in pertussis (3.5-4 year period) and measles (3-year period), before vaccination, corroborate theoretical predictions about the dynamics of these diseases, whereas absence of long-term oscillations in diphtheria is probably due to the influential presence of carriers upon the dynamics of the disease. Mass vaccination strongly suppressed disease incidence, did not eliminate seasonal oscillations, and appeared to have acted to lengthen long-term periodicity in pertussis and measles.
2010
Autores
Bressan, N; Amorim, P; Nunes, C; Moreira, AP;
Publicação
EUROPEAN JOURNAL OF ANAESTHESIOLOGY
Abstract
2010
Autores
Petry, MR; Moreira, AP; Braga, RAM; Reis, LP;
Publicação
2010 IEEE Conference on Robotics, Automation and Mechatronics, RAM 2010
Abstract
Intelligent wheelchairs operating in dynamic environments need to sense its neighborhood and adapt the control signal, in real-time, to avoid collisions and protect the user. In this paper we propose a robust, real-time obstacle avoidance extension of the classic potential field methodology. Our algorithm is specially adapted to share the wheelchair's control with the user avoiding risky situations. This method relies on the idea of virtual forces, generated by the user command (attractive force) and by the objects detected on each ultrasonic sensor (repulsive forces), acting on the wheelchair. The resultant wheelchair's behavior is obtained by the sum of the attractive force and all the repulsive forces at a given position. Experimental results from drive tests in a cluttered office environment provided statistical evidence that the proposed algorithm is effective to reduce the number of collisions and still improve the user's safety perception. ©2010 IEEE.
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