Abstract
Magnetic Resonance Imaging (MRI) exams suffer from undesirable structure replicating and overlapping effects on certain acquisition settings. These are called Spatial Aliasing Artefacts (SAA) and their presence interferes with the segmentation of other anatomical structures. This paper addresses the segmentation of the SAA in T1-weighted MRI image sets, in order to effectively remove their influence over the legitimately positioned body structures. The proposed method comprises an initial thresholding, employing the Triangle method, an aggregation of neighboring voxels through Region Growing. Further refinement of the objects contour is obtained with Convex Hull and a Minimum Path algorithm applied to two orthogonal planes (Sagittal and Axial). Some experiments concerning the extension of the pipeline used are reported and the results seem promising. The average contour distance concerning the Ground Truth (GT) rounds 2.5mm and area metrics point out average overlaps above 64% with the GT. Some issues concerning the fusion between the output from the two planes are to be perfected. Nevertheless, the results seems sufficient to neutralize the influence of SAA and expedite the downstream anatomical segmentation tasks.

Abstract
Surveillance missions in vast, difficult access environments are responsible for logistic difficulties in comparison to using an in loco monitoring team. For this and many other reasons, solutions with robotic platforms such as unmanned aerial vehicles (UAVs), present economic advantages. © 1986-2012 IEEE.

Abstract
Localized plasmons in metallic nanostructures present strong analogies with Quantum Mechanical problems of particles trapped in potential wells. In this paper we take this analogy further using the Madelung Formalism of Quantum Mechanics to express the fluid equations describing the charge density of the conduction electrons and corresponding interaction with light in terms of an effective generalized Non-linear Schrodinger equations. Within this context, it is possible to develop the analogy of a plasmonic atom and molecule that exhibits Rabi oscillations, Stark effect, among other Quantum Mechanical effects.

Abstract
Unmanned Aerial Vehicles (UAVs) have become a prominent research field due to their vast applicability and reduced size. An appealing aspect of theUAVs is the ability to accomplish autonomous flights in several contexts and purposes, and a variety of applications have been developed, from military to civilian fields. The system proposed in this work is a novel and simplified interaction between the user and the UAV for autonomous flight, where the necessary computation is performed in an embedded computer, decreasing response time and eliminating the necessity of long-distance communication links with base stations. Results are presented with both hardware in the loop simulations and a real UAV using Pixhawk, and Odroid and ROS as companion computer and software platform for code development. © Springer International Publishing Switzerland 2017.

Abstract
Traditional coverage path planners create lawnmower-type paths in the operating area completely ignoring the uncertainty in the vehicle's position. However, in the presence of significant uncertainty in localization estimates, one can no longer guarantee that the vehicle will cover all the area according to plan. Aiming to bridge this gap, we present a coverage path planning technique for search operations which takes into account the vehicle's position and detection performance uncertainties and tries to minimize this uncertainty along the planned path. The objective is to plan paths, using a localization error model as input, to reduce as much uncertainty as possible and to minimize the extra path length (swath overlap) while satisfying mission feasibility constraints. We introduce an algorithm that calculates what will be the best moments for bringing the vehicle to surface to ensure a bounded position error. We also consider time and energy constraints that may influence the planned trajectory as path overlap is increased to account for uncertainty. Additionally we challenge the assumption frequently seen in coverage algorithms where two observations of the same target are considered independent. © 2017 IEEE.

Abstract
The DC/DC boost converter is described as a time variant system. State-Space is one of the methods used to approach a time variant system to an invariant time linear system. The present document focuses on a comparative approach of output voltage regulation and system stability and performance. For this document, there were made MatLab tests of PI and PD controllers, with and without fuzzy control.