Abstract
This paper introduces the concept of energy debt: a new metric, reflecting the implied cost in terms of energy consumption over time, of choosing a flawed implementation of a software system rather than a more robust, yet possibly time consuming, approach. A flawed implementation is considered to contain code smells, known to have a negative influence on the energy consumption. Similar to technical debt, if energy debt is not properly addressed, it can accumulate an energy "interest". This interest will keep increasing as new versions of the software are released, and eventually reach a point where the interest will be higher than the initial energy debt. Addressing the issues/smells at such a point can remove energy debt, at the cost of having already consumed a significant amount of energy which can translate into high costs. We present all underlying concepts of energy debt, bridging the connection with the existing concept of technical debt and show how to compute the energy debt through a motivational example. © 2020 ACM.

Abstract
This work focuses on a reservoir with water leaks since its construction, the Beninar reservoir. The purpose of this reservoir was to regulate the Adra River basin, lying between the provinces of Almeria and Granada, and located south of Sierra Nevada Mountains (in the Inner Zones of the Betic Cordilleras, SE Spain). This basin extends over 746 km(2), at an altitude of 2780 m, with a very rough terrain and frequent torrential water flow. Due to the continuous extension of greenhouses in the east and west parts of Almeria, the water demand for agriculture and urban consumption increases day by day. As a consequence, aquifers are being overexploited, causing the current system to not be sustainable for a long time, that is, the storage capacity of the underground media and their possible contributions to an efficient management of resources have not been adequately taken into account. The Beninar dam has always had problems with water leaks. The dam was built even knowing that the land was not the most suitable, due to the frequent earth movements that took place in the town of Beninar, which was submerged beneath the waters of the reservoir. In this work, we process multi-temporal SAR datasets coming from the C-band satellites ERS-1/2, Envisat, and Sentinel-1A/B using MT-InSAR techniques, being able to monitor the deformation behavior of this dam for a long time period of more than 25 years, from 1992 to 2018.

Abstract
Object detection in the traffic domain has faced growing relevance through the years in developing autonomous driving mechanisms. As with vehicles, pedestrians face a very dynamic context, and identifying relevant objects from a pedestrian perspective presents many challenges. Improving the detection of some objects, such as crosswalks, is very relevant in this regard. This paper presents a technique that applies a computer vision approach to automatically generate datasets for training YOLO-based deep learning algorithms. An initial precision of 0.82 achieved with the generated dataset, which is increased to 0.84 after manually removing incorrect annotations. Results show that our approach leverages the dataset building process by reducing the manual workload needed. The approach could be used for training other object detection models used in traffic scenarios. © 2020, Springer Nature Switzerland AG.

Abstract
Nowadays, many drone models are available, designed for the most diverse applications. However, the various models fall into one of two types of drone: multi-copter or fixed-wing. The first type of drone consumes a lot of energy, since motors have to turn during all the flight. The former type of drone, in general needs a runway to take-off and landing. Moreover, they fly fast and cannot be motionless, which is unsuitable for many applications. In this paper we present a new paramotor drone, conceived and designed to overcome the highlighted limitations and to be a low-cost solution adapted for most applications. The selection of the various components of the presented prototype was based on a very thorough study, considering aerodynamic and efficiency criteria.

Abstract
A Internet das Coisas (IoT ou Internet of Things) tem se revelado uma tecnologia potencialmente disruptiva em vários campos da atividade  humana, o que inclui os processos educacionais. O processamento de dados produzidos e armazenados por objetos cotidianos e sensores e processados na web pode potencializar a análise pedagógica do professor e conferir maior liberdade para intervir nos percursos formativos dos alunos. Contudo, as pesquisas relacionando IoT e educação são incipientes, não conferindo uma visão clara sobre como concretizar este potencial. Este artigo apresenta uma revisão sistemática da literatura para melhor evidenciar as possibilidades de conexão entre IoT e Educação, recolhendo produções e analisando o conteúdo das mesmas e agrupando-as por ano e país de publicação,  contexto e nível educacional, foco dos estudos, tecnologias adotadas, aspectos metodológicos, aspectos teóricos e desenvolvimento de competências proporcionado por tais tecnologias. Constatou-se que a  maioria das pesquisas foca em aspectos técnicos e utilitários da IoT, mas existem propostas com referencial teórico-metodológico de caráter pedagógico. Os resultados apontam para a necessidade de aprofundamento da interligação entre Internet das Coisas e Educação, indicam possibilidades de pesquisas futuras e a quais áreas esse aprofundamento deve atender, possibilitando a utilização desse potencial tecnológico para a promoção de novas abordagens na área de ensino e aprendizagem.

Abstract
Training with Virtual Reality (VR) can bring several benefits, such as the reduction of costs and risks. We present an experimental study that aims to evaluate the effectiveness of a Virtual Environment (VE) to train firefighters using an innovative approach based on a Real Environment (RE) exercise. To measure the VE's effectiveness we used a Presence Questionnaire (PQ) and participant's cybersickness, stress and fatigue. Results from the PQ showed that participants rated the VE with high spatial presence and moderate realness and immersion. Signs of stress, analyzed from participant's Heart-Rate Variability, were shown in the RE but not in the VE. In the remaining variables, there was only an indicative difference for fatigue in the RE. Therefore, the results suggest that although our training VE was successful in giving participants spatial presence and in not causing cybersickness, its realness and immersion provided were not enough to provoke a similar RE response.