Abstract
This paper presents an Android application to help in the teaching of Fourier series expansions in undergraduate Electrical Engineering. Consequently, it discusses the teaching of Fourier series concepts in connection with undergraduate Electrical Engineering education; some of the basic Fourier series theory is briefly reviewed. The presented Android application has been found useful in this context. As expected, the application has an easy-to-use, friendly interface, and can be viewed as a tool to help undergraduate students test and assess the Fourier series expansions on a typical set of signals, whose analytical Fourier series coefficients were found during the theoretical lectures. Additionally, some of its main characteristics include the ability for the students to control the total approximation error and the number of terms/harmonics used in the expansion.

Abstract
In this paper the first steps for the derivation of a mathematical model to describe the mechanical behaviour of a cylindrical electromagnetic vibration energy harvester, designed to extract energy from human gait to power biomedical implantable devices, are provided. As it is usual, in the modelling of such devices, the proposed mechanical model is also based on the solution of Newton's second law, but here a nonlinear closed-form expression is used for the resulting magnetic force of the system, unlike what has been done in previous works where, traditionally, that expression is a linear or is a nonlinear approximation of the real one. The main feature of this mechanical model is that it depends on several parameters which are related to the main characteristics of this kind of devices, which constitutes a major advantage with respect to the usual models available in the literature since these characteristics can always be changed in order to optimize the device.

Abstract
Develop ground robots for crop monitoring and harvesting in steep slope vineyards is a complex challenge. Because of two main reasons: harsh condition of the terrain and unstable localization accuracy got from Global Positioning Systems (GPS). This paper presents a hybrid SLAM (VineSLAM) considering low cost landmarks to increase the robot localization accuracy, robustness and redundancy on these steep slope vineyards. Also, we present a cost-effective robot to carry-out crop monitoring tasks in steep slope vineyard environment. Test results got in a simulated and in a real test case supports the proposed approach and robot.

Abstract
The usage of small-sized unmanned aerial systems (UAS) has increased in the last years, in many different areas, being agriculture and forestry those who benefit the most from this relatively new remote sensing platform. Leaf area index, canopy and plant volume are among the parameters that can be determined using the very high resolution aerial data obtained by sensors coupled in unmanned aerial vehicles (UAV). This remote sensing technology affords the possibility of monitoring the vegetative development, identifying different types of issues, enabling the application of the most appropriated treatments in the affected areas. In this paper, a methodology allowing to perform multi-temporal UAS-based data analysis obtained by different sensors is proposed. A case study in vineyards and chestnuts is used to prove the benefits of continuous crop monitoring in its management and productivity of agroforestry parcels/activities. (C) 2017 The Authors. Published by Elsevier B.V.

Abstract
Develop ground robots for crop monitoring and harvesting in steep slope vineyards is a complex challenge due to two main reasons: harsh condition of the terrain and unstable localization accuracy got from Global Positioning Systems (GPS). For this context, a reliable localization system requires a high density of natural/artificial features and an accurate detector. This paper presents a novel visual detector for Vineyards Trunks and Masts (ViTruDe). The ViTruDe detector was developed considering the constrains of a cost-effective robot to carry-out crop monitoring tasks in steep slope vineyard environment. The obtained results with real data shows an accuracy higher than 95% for all tested configurations. The training and test data are made public for future research work. This approach is a contribution for an accurate and reliable localization system that is GPS-free.

Abstract
Prior knowledge of possible routes is undoubtedly an added value for autonomous navigation in irregular agricultural terrains. This information is particularly important when it involves the navigation of a monitoring robot, which necessarily carries a wide range of expensive sensors and when the vineyard presents a non-uniform configuration and extends over a very highly uneven terrain. In such case, a small navigation positional error can result in a large vertical deviation and consequently, a serious fall, which may damage or even destroy the robot. This article presents an automated way of deriving possible routes in this kind of terrain using three curve-skeleton algorithms for the 3D surfaces of the vineyard where the robot may navigate. The skeleton curves and real trajectory were represented in a graphical user OpenGL application developed for this purpose. A thinning, a geometric and a distance field algorithm were used for this study. The skeleton curves were compared with a real navigation path made by an expert when driving a tractor while spraying of the vineyard. In order to meet expert recommendations, the thinning algorithm was validated as the most suitable to achieve the aim of the study as it minimizes the quadratic average distance function applied to the skeleton points and the real trajectory. The limits of the most suitable curve-skeleton will be used as decision making points to establish navigation criteria for next step path planning.