Abstract
Unmanned Aerial Systems (UAS) are becoming more attractive in diverse applications due to their efficiency in performing tasks with a reduced time execution, covering a larger area, and lowering human risks at harmful tasks. In the context of Oil & Gas (O&G), the scenario is even more attractive for the application of UAS for inspection activities due to the large extension of these facilities and the operational risks involved in the processes. Many authors proposed solutions to detect gas leaks regarding the onshore unburied pipeline structures. However, only a few addressed the navigation and tracking problem for the autonomous navigation of UAS over these structures. Most proposed solutions rely on traditional computer vision strategies for tracking. As a drawback, depending on lighting conditions, the obtained path line may be inaccurate, making a strategy to force the UAS to continue on the path necessary. Therefore, this research describes the potential of an autonomous UAS based on image processing technique and Convolutional Neural Network (CNN) strategy to navigate appropriately in complex unburied pipeline networks contributing to the monitoring procedure of the Oil & Gas Industry structures. A CNN is used to detect the pipe, while image processing techniques such as Canny edge detection and Hough Transform are used to detect the pipe line reference, which is used by a line following algorithm to guide the UAS along the pipe. The framework is assessed by a PX4 flight controller Software-in-The-Loop (SITL) simulations performed with the Robot Operating System (ROS) along with the Gazebo platform to simulate the proposed operational environment and verify the approach's functionality as a proof of concept. Real tests were also conducted. The results showed that the solution is robust and feasible to deploy in this proposed task, achieving 72% of mean average precision on detecting different types of pipes and 0.0111 m of mean squared error on the path following with a drone 2 m away from a tube.

Abstract
In recent years the Internet of Things, in addition to use cases in 'smart cities', has also increasingly been used in precision agriculture. As in the rest of the world, it has been a growing reality in Portugal. In an agricultural environment, where energy resources can be scarce and dispersed, the implementation of a LoRa network with autonomous sensor nodes must consider the limitations imposed by the energy consumed by the sensor node, when powered by a battery and a solar panel. For this, experimental tests must be carried out so that there is enough data for the implementation and optimization of the devices. This article presents a work focused on the study of the autonomy and energy efficiency of the sensor device, using algorithms capable of managing energy consumption as a function of the luminosity of the place. Preliminary results attest to the relevance of this approach, keeping the sensor node in operation without interruptions.

Abstract

Abstract
In the current Industry 4 [...]

Abstract
User experience can be affected by the amount and intensity of information presented. Four scenarios were developed to assess the insertion of information elements (chronometer and hint system) and tested with 37 users to find out if they affected the user's sense of presence and symptoms of cybersickness. In order to instruct users and using virtual reality using the Unity 3D game engine, we created a virtual world where the user has the role of exploring the environment and looking for mushrooms, and can consult a description about it. For tests with users, the IPQp and SSQ questionnaires were applied. The results indicate that it is possible to create a virtual world with the addition of informational components without significantly disturbing the user experience.

Abstract
Construction and analysis of distributed systems is difficult. Multiparty session types (MPST) constitute a method to make it easier. The idea is to use type checking to statically prove deadlock freedom and protocol compliance of communicating processes. In practice, the premier approach to apply the MPST method in combination with mainstream programming languages has been based on API generation. In this paper (pearl), we revisit and revise this approach. Regarding our “revisitation”, using Scala 3, we present the existing API generation approach, which is based on deterministic finite automata (DFA), in terms of both the existing states-as-classes encoding of DFAs as APIs, and a new states-as-type-parameters encoding; the latter leverages match types in Scala 3. Regarding our “revision”, also using Scala 3, we present a new API generation approach that is based on sets of pomsets instead of DFAs; it crucially leverages match types, too. Our fresh perspective allows us to avoid two forms of combinatorial explosion resulting from implementing concurrent subprotocols in the DFA-based approach. We implement our approach in a new API generation tool. © Guillermina Cledou, Luc Edixhoven, Sung-Shik Jongmans, and Jos Proena; licensed under Creative Commons License CC-BY 4.0