Abstract
Serious Games have been used in professional training to increase employee engagement and improve the results of training initiatives in this context. This work intends to investigate the influence of game elements, in adaptable Serious Games, according to the users' interactions, in the increase of engagement in the game itself and, as the main objective, in the learning outcomes and the transfer of the acquired knowledge and practised skills to activities in the daily work. Using the Design Science Research methodology, this study is intended to develop a framework for the development and evaluation of Serious Games to improve the user experience, the learning outcomes, the transfer of knowledge to work situations, and the application of skills practised in the game in real professional scenarios. © 2021 Associacao Portuguesa de Sistemas de Informacao. All rights reserved.

Abstract
Traditional post-hoc high-fidelity scientific visualization (HSV) of numerical simulations requires multiple I/O check-pointing to inspect the simulation progress. The costs of these I/O operations are high and can grow exponentially with increasing problem sizes. In situ HSV dispenses with costly check-pointing I/O operations, but requires additional computing resources to generate the visualization, increasing power and energy consumption. In this paper we present LOOM, a new interweaving approach supported by a task scheduling framework to allow tightly coupled in situ visualization without significantly adding to the overall simulation runtime. The approach exploits the idle times of the numerical simulation threads, due to workload imbalances, to perform the visualization steps. Overall execution time (simulation plus visualization) is minimized. Power requirements are also minimized by sharing the same computational resources among numerical simulation and visualization tasks. We demonstrate that LOOM reduces time to visualization by 3 × compared to a traditional non-interwoven pipeline. Our results here demonstrate good potential for additional gains for large distributed-memory use cases with larger interleaving opportunities. © 2021 ACM.

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Abstract
The big growth of electrical demand by the countries required larger and more complex power systems, which have led to a greater need for monitoring and maintenance of these systems. To overcome this problem, UAVs equipped with appropriated sensors have emerged, allowing the reduction of the costs and risks when compared with traditional methods. The development of UAVs together with the great advance of the deep learning technologies, more precisely in the detection of objects, allowed to increase the level of automation in the process of inspection. This work presents an electrical assets monitoring system for detection of insulators and structures (poles and pylons) from images captured through a UAV. The proposed detection system is based on lightweight Convolutional Neural Networks and it is able to run on a portable device, aiming for a low cost, accurate and modular system, capable of running in real time.

Abstract
This case study presents a virtual reality experts' evaluation of a desktop-based virtual world developed towards distance education, under the perspectives of usability and sense of presence, which are considered factors that can potentially influence learning outcomes. Among the results, data from usability and sense of presence were positively correlated. The sense of presence was achieved, with participants losing track of time while performing the activity. Experts agreed that the virtual world is easy to use and can prepare students for the real-world task. The findings outline positive and negative points that must be addressed in order to optimize the experience of distance education students.

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