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.

Abstract
This study explored the viability of out-the-box, pre-trained ConvNet models as a tool to generate features for large-scale classification tasks. A juxtaposition with generative methods for vocabulary generation was drawn. Both methods were chosen in an attempt to integrate other datasets (transfer learning) and unlabelled data, respectively. Both methods were used together, studying the viability of a ConvNet model to estimate category labels of unlabelled images. All experiments pertaining to this study were carried out over a two-class set, later expanded into a 5-category dataset. The pre-trained models used were obtained from the Caffe Model Zoo. The study showed that the pre-trained model achieved best results for the binary dataset, with an accuracy of 0.945. However, for the 5-class dataset, generative vocabularies outperformed the ConvNet (0.91 vs. 0.861). Furthermore, when replacing labelled images with unlabelled ones during training, acceptable accuracy scores were obtained (as high as 0.903). Additionally, it was observed that linear kernels perform particularly well when utilized with generative models. This was especially relevant when compared to ConvNets, which require days of training even when utilizing multiple GPUs for computations.

Abstract
This work explores the application of information technologies in the processes of mentoring, allowing to optimize them and adapting this service of mentoring, to the current reality. It is intended to understand the importance of e-mentoring for the improvement and achievement of objectives for both apprentices and mentors, in which it shows how the relationship between both should be done, in order to be able to communicate with knowledge sharing throughout the relationship, from its beginning to its closure.

Abstract
Sous vide cook-chill (SVCC) is characterized by vacuum-packaging raw or partially prepared foods before pasteurization, followed by rapid chilling and storage below 3C. The application of essential oils (EOs) to food products is a suitable strategy to control pathogens and to extend their shelf life by reducing microbial levels and oxidative processes. The aim of this study was to evaluate the efficacy of Rosmarinus officinalis L. (rosemary) and Thymus vulgaris L. (thyme) EOs against Listeria monocytogenes ATCC 679, inoculated in beef processed by SVCC stored at 2 and 8C for 1, 2, 3, 7, 14, 21 and 28 days. The composition of EOs was identified by gas chromatography-mass spectrometry analysis. The main compounds identified in rosemary EO were eucalyptol (13.05%), camphor (8.93%), verbenone (8.58%), endo-borneol (7.87%) and alpha-pinene (6.78%) and in thyme EO were linalool (18.18%), thymol (7.48%), limonene (6.49%), endo-borneol (5.86%) and terpinen-4-ol (5.66%). Using the minimum inhibitory concentration (MIC) method, L. monocytogenes was inhibited at 3.9 mu L/mL to thyme EO and at 62.5 mu L/mL to rosemary EO. Beef samples of M. longissimus thoracis et lumborum were packaged in bags, inoculated and one of each EO was added at MIC values. Bags were vacuum-sealed and samples were processed at 55C/65 min for 3log(10) CFU/g reduction. A reduction of the counts of L. monocytogenes was observed in all samples at 2C. At 8C counts of L. monocytogenes were almost similar in control samples and those with thyme EO with an increase of themicrobial counts since day 7. Inversely, counts of L. monocytogenes in beef samples with rosemary EO stored at 2 and 8C decreased about 2 log(10) CFU. These results support the possibility of using rosemary EO as natural preservative due to its antimicrobial effect against L. monocytogenes. Also, our results confirm that an adequate chilling storage is essential to guarantee the safety of SVCC product regarding L. monocytogenes to avoid foodborne outbreaks.

Abstract
Collaborative working as well as sharing resources and knowledge represent key points in today's development in all fields, including education. Know-how transfer and collaboration in learning and teaching are aspects promoted and sustained by institutional management as well as the European initiatives. Thus, leading to the idea of a federation which will facilitate engineering education. A consortium formed by five European universities decided to join efforts to provide to the community a federation, which could be used by different stakeholders interest in teaching, learning or developing new skills in the field of electronics. The proposed remote system, Virtual Instruments System in Reality, or VISIR in short, offers the possibility of working with real equipment and obtain the real-world/real-time measurements. By developing such a VISIR federation some of the constraints of using remote labs, the ones associated with development and maintenance costs, and scalability, will be minimized. This paper aims to present the initial steps for developing a VISIR Federation, which is also the primary goal of PILAR Platform Integration of Laboratories based on the Architecture of visiR project.