Abstract
This work presents the development of a software for data acquisition and control (ASYS) on a clinical setup. Similar to the industrial Supervisory Control And Data Acquisition (SCADA) the software assembles a Target Controlled Infusion (TCI) monitoring and supervisory control data in real time from devices in a surgical room. The software is not a full controller since the TCI systems comprehend permanent interaction from the anesthesiologist Based on pharmacokinetic models, the effect-site and plasma concentrations can be related with the drug dose infused and vice versa. The software determines the infusion rates of the drug which are given as commands to the infusion pumps. This software provides the anesthesiologist with a trustworthy tool for managing a safe and balanced anesthesia. Since it also incorporates the acquisition and display of patients brain signals.

Abstract
This paper presents a nonlinear model based predictive controller (NMPC) for trajectory tracking of a mobile robot. Methods of numerical optimization to perform real time nonlinear minimization of the cost function are used. The cost function penalizes the robot position error, the robot orientation angle error and the control effort. Experimental results of the trajectories following and the performance of the methods of optimization are presented.

Abstract
We investigate the effects of diffusion on the evolution of steady-state dark and gray spatial solitons in biased photorefractive media. Numerical integration of the nonlinear propagation equation shows that the soliton beams experience a modification of their initial trajectory, as well as a variation of their minimum intensity. This process is further studied using perturbation analysis, which predicts that the center of the optical beam moves along a parabolic trajectory and, moreover, that its minimum intensity varies linearly with the propagation distance, either increasing or decreasing depending on the sign of the initial transverse velocity. Relevant examples are provided.

Abstract
Three-dimensional (3D) object reconstruction using only bi-dimensional (2D) images has been a major research topic in Computer Vision. However, it is still a complex problem to solve, when automation, speed and precision are required. In the work presented in this paper, we developed a computational platform with the main purpose of building 3D geometric models from uncalibrated images of objects. Simplicity and automation were our major guidelines to choose volumetric reconstruction methods, such as Generalized Voxel Coloring. This method uses photo-consistency measures to build an accurate 3D geometric model, without imposing any kind of restrictions on the relative motion between the camera used and the object to be reconstructed. Our final goal is to use our computational platform in building and characterize human external anatomical shapes using a single off-the-shelf camera.

Abstract
The efficiency of network attachment plays a crucial role in the performance of accessing services in new environments. As an example, when a moving network is changing its location relative to attachment points, the detection of the candidate access networks along with their properties and security relationships needs to be carefully managed. This paper presents the framework and mechanisms for network attachment of Ambient Networks. Different steps required for optimizing the network attachment procedure are studied, and a secure network attachment protocol is proposed.

Abstract
Consider a wireless sensor network (WSN) where a broadcast from a sensor node does not reach all sensor nodes in the network; such networks are often called multihop networks. Sensor nodes take sensor readings but individual sensor readings are not very important. It is important however to compute aggregated quantities of these sensor readings. The minimum and maximum of all sensor readings at an instant are often interesting because they indicate abnormal behavior for example if the maximum temperature is very high then it may be that afire has broken out. We propose an algorithm for computing the min or max of sensor reading in a multihop network. This algorithm has the particularly interesting property of having a time complexity that does not depend on the number of sensor nodes; only the network diameter and the range of the value domain of sensor readings matter