Abstract
The blue economy potential is envisioned to increase the activity at the ocean worldwide in the coming years. To support these activities and the convergence to the Internet of Moving Things, Unmanned Surface Vehicles (USVs) are considered viable platforms to enable a large number of missions, including border surveillance and environmental monitoring. Typically, USVs use Wi-Fi for communicating with shore. However, in the literature, there is a lack of studies characterizing the shore-to-USV Wi-Fi link. This paper studies the influence of distance and USV orientation on the shore-to-USV link quality at the 2.4 GHz and 5.8 GHz Industrial, Scientific, and Medical (ISM) bands. The study is supported by experimental results, collected during sea trials. For the 2.4 GHz band, we conclude that neither the Two-Ray propagation model nor the Friis propagation model allow a good fit to the experimental measurements. On the other hand, for the 5 GHz band, the Friis propagation model fits the obtained experimental results. © 2018 IEEE.

Abstract
In wireless networking R&D we typically depend on experimentation to further evaluate a solution, as simulation is inherently a simplification of the real-world. However, experimentation is limited in aspects where simulation excels, such as repeatability and reproducibility. Real wireless experiments are hardly repeatable. Given the same input they can produce very different output results, since wireless communications are influenced by external random phenomena such as noise, interference, and multipath. Real experiments are also difficult to reproduce due to testbed operational constraints and availability. We have previously proposed the Trace-based Simulation (TS) approach, which uses the TraceBasedPropagationLossModel to successfully reproduce past experiments. Yet, in its current version, the TraceBasedPropagationLossModel only supports point-to-point scenarios. In this paper, we introduce a new version of the model that supports Multiple Access wireless scenarios. To validate the new version of the model, the network throughput was measured in a laboratory testbed. The experimental results were then compared to the network throughput achieved using the ns-3 trace-based simulation and a pure ns-3 simulation, confirming the TS approach is valid for multiple access scenarios too.

Abstract
The availability of low cost networked wireless devices and video cameras is enabling wireless video sensor networks (WVSNs), which can be used in scenarios such as healthcare, agriculture, smart cities, intelligent transportation systems, and surveillance. These scenarios typically require that each node sends a video stream to a server located in the cloud. The IEEE 802.11 is considered a suitable technology for transmitting video wirelessly, as it supports high data rates. However, when using a multi-hop topology to extend the IEEE 802.11 coverage, the IEEE 802.11-based WVSNs suffer from three problems: low network capacity, throughput unfairness, and energy inefficiency. To overcome these problems, we propose a holistic solution, named Green wiReless vidEo sENsor NEtworks uSing out-of-band Signalling (GREENNESS). GREENNESS combines a node polling mechanism with the use of out-of-band signaling over a low power radio to signal when a video sensor should switch ON and OFF its IEEE 802.11 interface, thus saving energy. The results obtained for random network topologies show that GREENNESS can achieve energy savings up to 92%, and improve network capacity and throughput fairness when compared to state of the art CSMA/CA-based WVSN solutions.

Abstract
The support of video in the learning environment is nowadays used to many ends, either for demonstration, research or share. It is intended to reinforce the space before and after class and introduce a new dynamic and interaction in the classroom itself. Pedagogical innovation may be achieved by different approaches to motivate students and obtain better results. This paper presents a revision of the literature about the potential of using video annotation in the education context, specifically in the domain of Physics, using an open source annotation tool. The creation of audiovisual references, either for quick access to parts of organized video annotated content by the teacher, knowledge building or revision by and for other students is analyzed. This study is complemented with a testbed, showing the potential of using audiovisual annotated content, within a k-12 context. Students were invited to select video content, annotate, organize and publish the annotations, which could support the learning process in the domain of Physics. Results show that most of the aspects under analysis received a positive evaluation. The only exception relates to the capacity of the approach to motivated students to the study of Physics, as most of the students did not see this methodology as a motivating means.

Abstract
Process variations in MOS manufacturing processes tend to increase within each new technology node, leading to lower production yields, particularly those of analogue circuits, which are also sensitive to external perturbations that might force there performance to drift beyond there admissible tolerance margins. This issue is addressed here with the design of a calibratable N-Integer phase-locked loop (PLL) based frequency synthesizer. In the approach being proposed, a statistical analysis is carried out to know the sensitivity of the PLL performance to expected process, temperature, and voltage variations. A training data set is then identified and used to define the calibration law and the required calibration algorithm. Simulation results are presented that confirm its validity.

Abstract
Panoramic or aerial images can be acquired with some easiness and cover vast tracts of territory to be used in fire detection. The analysis of these images, in particular based on color and threshold indices, can be very interesting computationally when applied in real time systems and collected, for example, through drones or watchtowers. This paper presents a solution designated Color Algorithm for Flame Exposure (CAFE), which significantly improves an existing method (cf. Forest Fire Detection Index - FFDI) in flame detection, based on daylight images, in mixed Mediterranean landscape, containing vegetation, buildings, burning areas, land, etc. The CAFE approach, presented, adds a parameterizable transformation of the image into the Lab color space. This approach was tested in four distinct scenarios, significantly reducing false positives and maintaining an equivalent level of false negatives when compared to the FFDI approach.