Abstract
A 253km ultralong remote displacement sensor system based on a fiber loop mirror interrogated by a commercial optical time-domain reflectometer is proposed and experimentally demonstrated. The use of a fiber loop mirror increases the signal-to-noise ratio, allowing the system to interrogate sensors placed 253km away from the monitoring system without using any optical amplification. The displacement sensor was based on a long period grating spliced inside of the loop mirror, which modifies the mirror reflectivity accordingly to the applied displacement. (C) 2011 Optical Society of America

Abstract
We discuss recent developments in signal processing techniques for post-compensation of fiber dispersion and nonlinear distortion in both coherent and radio-over-fiber optical systems.

Abstract
This paper presents the modifications needed to adapt a humanoid agent architecture and behaviors from simulation to a real robot. The experiments were conducted using the Aldebaran Nao robot model. The agent architecture was adapted from the RoboCup 3D Simulation League to the Standard Platform League with as few changes as possible. The reasons for the modifications include small differences in the dimensions and dynamics of the simulated and the real robot and the fact that the simulator does not create an exact copy of a real environment. In addition, the real robot API is different from the simulated robot API and there are a few more restrictions on the allowed joint configurations. The general approach for using behaviors developed for simulation in the real robot was to: first, (if necessary) make the simulated behavior compliant with the real robot restrictions, second, apply the simulated behavior to the real robot reducing its velocity, and finally, increase the velocity, while adapting the behavior parameters, until the behavior gets unstable or inefficient. This paper also presents an algorithm to calculate the three angles of the hip that produce the desired vertical hip rotation, since the Nao robot does not have a vertical hip joint. All simulation behaviors described in this paper were successfully adapted to the real robot.

Abstract
In this paper, we consider the problem of separating a set of independent components when only one movable sensor is available to record the mixtures. We propose to exploit the quasi-periodicity of the heart signals to transform the signal from this one moving sensor, into a set of measurements, as if from a virtual array of sensors. We then use ICA to perform source separation. We show that this technique can be applied to heart sounds and to electrocardiograms.

Abstract
We address necessary conditions of optimality (NCO), in the form of a maximum principle, for optimal control problems with state constraints. In particular, we are interested in the NCO that are strengthened to avoid the degeneracy phenomenon that occurs when the trajectory hits the boundary of the state constraint. In the literature on this subject, we can distinguish two types of constraint qualifications (CQ) under which the strengthened NCO can be applied: CQ involving the optimal control and CQ not involving it. Each one of these types of CQ has its own merits. The CQs involving the optimal control are not so easy to verify, but, are typically applicable to problems with less regularity on the data. In this article, we provide conditions under which the type of CQ involving the optimal control can be reduced to the other type. In this way, we also provide nondegenerate NCO that are valid under a different set of hypotheses.

Abstract
Decision making in complex, multi agent and dynamic environments such as disaster spaces is a challenging problem in Artificial Intelligence. Uncertainty, noisy input data and stochastic behavior which are common characteristics of such environment makes real time decision making more complicated. In this paper an approach to solve the bottleneck of dynamicity and variety of conditions in such situations based on reinforcement learning is presented. This method is applied to RoboCup Rescue Simulation Fire brigade agent's decision making process and it learned a good strategy to save civilians and city from fire. The utilized method increases the speed of learning and it has very low memory usage. The effectiveness of the proposed method is shown through simulation results.