Abstract
Precision viticulture (PV) and precision agriculture (PA) requires the acquisition and processing of a vast collection of data coming typically from large scale and heterogeneous sensor networks. Unfortunately, sensor integration is far from being simple due to the number of incompatible network specifications and platforms. The adoption of a common, standard communication interface would allow the engineer to abstract the relation between the sensor and the network. This would reduce the development efforts and emerge as an important step towards the adoption of "plug-and-play" technology in PA/PV sensor networks. This paper explores this need and introduces a framework for smart data acquisition in PA/PV that relies on the IEEE 1451 family of standards, which addresses the transducer-to-network interoperability issues. The framework includes a ZigBee end device (sMPWiNodeZ),,as an IEEE 1451 WTIM (Wireless Transducer Interface Module), and an IEEE 1451 NCAP (Network Capable Application Processor) that acts as gateway to an information service provider and WSN (Wireless Sensor Network) coordinator. The paper discusses the proposed IEEE 1451 system architecture and its benefits in PA/PV and closes with results/lessons learned from in-field trials towards smarter WSN.

Abstract
Traditional imageryprovided, for example, by RGB and/or NIR sensorshas proven to be useful in many agroforestry applications. However, it lacks the spectral range and precision to profile materials and organisms that only hyperspectral sensors can provide. This kind of high-resolution spectroscopy was firstly used in satellites and later in manned aircraft, which are significantly expensive platforms and extremely restrictive due to availability limitations and/or complex logistics. More recently, UAS have emerged as a very popular and cost-effective remote sensing technology, composed of aerial platforms capable of carrying small-sized and lightweight sensors. Meanwhile, hyperspectral technology developments have been consistently resulting in smaller and lighter sensors that can currently be integrated in UAS for either scientific or commercial purposes. The hyperspectral sensors' ability for measuring hundreds of bands raises complexity when considering the sheer quantity of acquired data, whose usefulness depends on both calibration and corrective tasks occurring in pre- and post-flight stages. Further steps regarding hyperspectral data processing must be performed towards the retrieval of relevant information, which provides the true benefits for assertive interventions in agricultural crops and forested areas. Considering the aforementioned topics and the goal of providing a global view focused on hyperspectral-based remote sensing supported by UAV platforms, a survey including hyperspectral sensors, inherent data processing and applications focusing both on agriculture and forestrywherein the combination of UAV and hyperspectral sensors plays a center roleis presented in this paper. Firstly, the advantages of hyperspectral data over RGB imagery and multispectral data are highlighted. Then, hyperspectral acquisition devices are addressed, including sensor types, acquisition modes and UAV-compatible sensors that can be used for both research and commercial purposes. Pre-flight operations and post-flight pre-processing are pointed out as necessary to ensure the usefulness of hyperspectral data for further processing towards the retrieval of conclusive information. With the goal of simplifying hyperspectral data processingby isolating the common user from the processes' mathematical complexityseveral available toolboxes that allow a direct access to level-one hyperspectral data are presented. Moreover, research works focusing the symbiosis between UAV-hyperspectral for agriculture and forestry applications are reviewed, just before the paper's conclusions.

Abstract
Video Games may be used with different applications in mind, for entertainment, training and simulation or even as teaching tools. However, the production of contents for such games, namely game scenarios with virtual worlds composed by cities and related elements (streets, buildings, furniture and so on) may require a laborious effort by multidisciplinary teams which lead to an expensive and time consuming solution. In order to avoid the development burden, procedural modeling techniques have been created and applied to generate virtual models of buildings and cities expeditiously with high degree of detail and realism. Nevertheless, most of the existing techniques use complex sets of rules to produce models without being aware of the architectonic structures and its relationships. Thereby, in order to simplify the generation process and rule dealing we propose, in this paper, an ontology-based procedural modeling methodology which integrates an ontological structure, describing city elements and the relationships between each other, and a combined set of procedural techniques to generate roman houses. The preliminary results point to a method capable of producing roman houses expeditiously, including the interiors and the exteriors.

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
Augmented Reality (AR) has been widely used in areas such as medicine, education, entertainment and cultural heritage to enhance activities that include (but are not limited to) teaching, training and amusement, through the completion of the real world with viewable and usually interactive virtual data (e.g. 3D models, geo-markers and labels). Despite the already confrmed AR benefts in the referred areas, many of the existing AR systems rely on heavy and obsolete hardware bundles composed of several devices and numerous cables that usually culminate in considerably expensive solutions. This issue is about to be tackled through the recent technological developments which currently enable the production of small-sized boards with remarkable capabilities - such as processing, visualization and storage - at relatively low prices. Following this line of reasoning, this paper proposes and compares fve different multi-purpose AR mobile units, running Windows or Android operating systems, having in mind low-cost and lightweight requirements and different levels of immersion: a laptop computer, two tablets, a smartphone and smartglasses. A set of tests was carried out to evaluate the proposed unit performance. Moreover, a set of users' assessments was also conducted, highlighting an overall acceptance regarding the use of the proposed units in AR applications. This paper is an extension of a previous work (Pádua et al., 2015) in which a conceptual architecture for mobile units - complying with AR requirements (including visualization, processing, location and communication) for indoor or outdoor utilization - was presented, along with a shorter set of lightweight and cost-effective AR mobile units and respective performance tests. Copyright © 2015,.

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.