Abstract
In lung cancer diagnosis, the design of robust Computer Aided Diagnosis (CAD) systems needs to include an adequate differentiation of benign from malignant nodules. This paper presents a CAD system for the classification of lung nodules in chest Computed Tomography (CT) scans as the way to diagnose lung cancer. The proposed method measures a set of 295 heterogeneous characteristics, including morphology, intensity or texture features, that were used as input of different KNN and SVM classifiers. The system was modeled and trained using a groundtruth provided by specialists taken from a public lung image dataset, the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). This image dataset includes chest CT scans with lung nodule location together with information about the degree of malignancy, among other properties, provided by multiple expert clinicians. In particular, the computed degree of malignancy try to follow the manual labeling by the different radiologists. Promising results were obtained with a first order SVM with an exponential kernel achieving an area under the receiver operating characteristic curve of 96.2 +/- 0.5% when compared with the groundtruth provided in the public CT lung image dataset.

Abstract
Water and energy are essential for human existence, and its rational use should be encouraged. According to the literature review, water consumption directly affects energy consumption and are inseparably linked resources. The energy to water part of the water/energy nexus, increasingly highlighted as an important issue for future planning and strategic policy considerations. Joint consideration of both water/energy domains can identify new options for increasing overall resource use efficiency. This work is part of the project ENERWAT that has as goal to measure in situ the water/energy consumption related with water supply end use in rural and urban dwellings in order to validate the data collected by survey. A methodology for low cost measure and store water/energy consumes was developed. Water, Gas and electricity data was stored in image format. In this paper, a CNN architecture was applied and trained to read water/energy. The models suited their proposed. The achieved accuracy for test set was: water - dozen: 0.98, unit: 0.92; gas: dozen: 0.94, unit: 0.99; and electricity - dozen: 0.99, units 0.99. The more challenge digit was water unit digit due to partial occlusion. It is presented a day of readings and discussed some events. (C) 2017 The Authors. Published by Elsevier B.V.

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
The aim of this study is twofold: first, to present a survey of the actual and most advanced methods related to the use of unmanned aerial systems (UASs) that emerged in the past few years due to the technological advancements that allowed the miniaturization of components, leading to the availability of small-sized unmanned aerial vehicles (UAVs) equipped with Global Navigation Satellite Systems (GNSS) and high quality and cost-effective sensors; second, to advice the target audience - mostly farmers and foresters - how to choose the appropriate UAV and imaging sensor, as well as suitable approaches to get the expected and needed results of using technological tools to extract valuable information about agroforestry systems and its dynamics, according to their parcels' size and crop's types. Following this goal, this work goes beyond a survey regarding UAS and their applications, already made by several authors. It also provides recommendations on how to choose both the best sensor and UAV, in according with the required application. Moreover, it presents what can be done with the acquired sensors' data through theuse of methods, procedures, algorithms and arithmetic operations. Finally, some recent applications in the agroforestry research area are presented, regarding the main goal of each analysed studies, the used UAV, sensors, and the data processing stage to reach conclusions.

Abstract
A methodology to rapidly produce environments that combine the intuition of in situ augmented reality (AR) with the commodity of virtual reality (VR) is proposed in this paper, by bringing together unmanned aerial systems (UAS) imagery and procedural modelling. While fully synthesized environments provide a very accurate visualization of the conserved parts of the real-world, missing parts - namely ruins - can be complemented with procedurally modelled structures. Regarding methodology's steps, firstly, a UAS flight mission gathers georeferenced imagery data about the site of interest. Then, the image set is converted to an accurate 3D model of the referred site, through photogrammetry. By considering the geographic information that also results from the previous process, ruins are manually outlined for georeferencing purposes. To complement ruins' missing information, virtual models of buildings are produced too, in a procedural modelling tool. Finally, at the full VR environment setup step, all elements are imported and subjected to geometric transformations that aim to match the procedurally modelled buildings with the outlined ruins. To improve the insight about the process work-flow, system's architecture and implementation are presented along with a case-study regarding a historically relevant site - Vila Velha's city gates (Vila Real, Portugal) - and preliminary results.

Abstract
This paper presents a model of a system capable of addressing the training needs identified by the University of Tras-os-Montes e Alto Douro (UTAD). In addition to supporting the typical needs of distance learning/education (e.g., e-learning), it is also intended that the proposed system will complement the traditional classroom-based teaching. This model will have two modules: the physical/infrastructural module and the policies/practices module. The physical/infrastructural module will have the following (control and management) components or modules: e-learning platforms (e.g., Moodle, Sakai) with SIDE (a platform for teaching support developed at UTAD) interconnection; website with educational/training offer and e-learning events; media repository; file storage and sharing service; collaborative/cooperative platform, for the sharing of information and knowledge; scientific repository, for the storage and sharing of work and scientific research, books, conferences, etc.; forum; ticket service/helpdesk, to help solving problems that may arise; Customer Relationship Management (CRM) service (management, relationship and customer satisfaction-student, teachers, other); Learning Analytics system (collection of information about the quality of teaching, evolution and student analysis in the e-learning mode, etc.). Additionally, there will be an assessment/examination space, a contents production studio, and a training studio. The policies/practices module includes the institution policies, and including policies for the creation/dissemination of curses, implementation of course evaluation strategies and continuous improvement, training policies, recognition of the merit and effort of teachers, the training in using the system, the policies for the creation of physical spaces equipped with the necessary tools (computers, cameras, video-conferencing, etc.), among other. In line with these, UTAD has come to recognize that e-learning should be part of its strategy for its training offer and, consequently, is being adopting new policies, namely through the signing of protocols with other institutions with more experience using e-learning. To achieve these objectives, a detailed review of other models and systems that have been successfully implemented in other international reference universities will also be presented here.