We show that, far from being a drawback, the ubiquitous presence of random vibrations in vision systems operating from mobile devices can advantageously be used as a fundamental tool for edge detection. Directly inspired by biology, the concept of dynamic retina uses the random spatiotemporal path, traced by a moving receptor that samples the image over time, as the basis for the edge detection operation. We propose a simple mathematical formalization of the dynamic retina concept that shows that the relevant information needed for edge detection is contained in the modulation of the variance of the output signal delivered by the retina. Based on a sequence of observations, we then use a variance estimator to determine the presence of the image edges. Following again a biological inspiration, more specifically focusing on neuron dynamics, we introduce a threshold type estimator and use its local asymptotic normality to optimize, via the Cramer-Rao relation, the value of the threshold. The optimal threshold value coincides with a maximum of the associated Fisher information and the overall process can therefore be directly interpreted as a stochastic resonance. We end our contribution by reporting some simple experimental illustrations.

We study the "Whittle relaxation" version of the continuous time, discrete, and continuous state space Restless Bandit problem under the discounted cost criterion. Explicit expressions of Whittle's priority indexes, which generalize the Gittins indexes, are derived. This formalism is then used in the context of flexible make-to-stock production to construct dynamic scheduling rules. These analytical results are finally compared with the optimal numerically derived policy, obtained for a server delivering two product types. It is observed that the Whittle relaxation version of the Restless Bandit model nearly yields optimal dynamic scheduling rules.

In the present contribution, we explore the scheduling rules and the hedging levels that can be obtained by using a restless bandit problem formulation of a make-to-stock production.

A new highly flexible components feeder used in automatic assembly lines is presented. Flexibility is gained by the joint use of a vision system and a vibrating tooling plate which simultaneously acts as a separating and an orienting mechanism. A detailed mathematical modeling of the dynamics is derived. The modeling fully takes into account the random nature of the mechanisms which are used to extract out of a bulk of randomly oriented parts, those exhibiting a prescribed orientation.

The variability factor, (i.e., the variance) of the cumulative production, /spl Sigma/(t), delivered by a line composed of failure prone machines is studied in the fluid modeling approach. In this context, the evolution of /spl Sigma/(t) is described by a stochastic differential equation in which the noise source describes the random failures of the machines. We calculate the fluctuations of the production for three different situations, namely for a single nonMarkovian machine, for unbuffered networks of Markovian machines and for production dipoles composed of two machines separated by one buffer. The dynamics of the production dipole is approached via the introduction of a random environment model. Thanks to this new model, we can explicitly take into account the buffer induced correlations phenomena which directly influence the variability of /spl Sigma/(t). The probabilistic properties of the random time needed to complete a batch of fixed size are also explicitly derived.