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Switch-mode power supplies usually emit electromagnetic interferences at the switching frequency and its harmonics. Inducing chaos in these systems has recently been suggested as a means of reducing these spectral emissions, yet at the expense of aggravating the overall magnitude of the ripple in the output voltage. We propose here a new nonlinear feedback, which induces chaos and which is able at the same time to achieve a low spectral emission and to maintain a small ripple in the output. The design of this new and simple controller is based on the propriety that chaotified nonlinear systems present many independent chaotic attractors of small dimensions.

This paper describes a learning routing system designed to ease the movement of emergency vehicles through a network of congested streets. Real-time capabilities of the routing system are given by the use of GPS equipment installed aboard of every emergency vehicle. The same type of equipment is used to control the state of traffic lights and to collect real-time data on the current traffic volume. The actual routing algorithm is part of the A* class and reaches decisions with the help of a neural network that estimates the expected time of arrival of every feasible route the emergency vehicles might follow. Real-time traffic data is used to train the neural network and to help the routing algorithm work faster. This not only reduces the response time but it also increases the safety of the emergency vehicles.

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