Abstract
Indoor localization systems are an important topic in the field of manufacturing process. A computational infrastructure based on Bluetooth low energy technology with state estimators for filtering is used to localize employees in the shop floor. The researchers' motivation is two-folds: implement an indoor tracking system while promoting manage production time. In this paper, we discuss the first prototype of a localization system adapted to address these goals. Experimental results show that the system for our case study, achieves a localization accuracy of less than three meters. © 2022 IEEE.

Abstract
Over the years, many techniques have been developed for the stabilisation of bone fractures. The study of the adhesion of bone-to-bone cement is an important step towards the development of new immobilization systems. Although bone cement has been used for more than fifty years, very few studies have been performed regarding the evaluation of fracture properties. In this work, numerical and experimental investigations were conducted to evaluate the strain energy release rate under mode I loading in a bone-cement bonded joint, using the Double Cantilever Beam (DCB) test. Cohesive zone laws were also measured combining the finite element method with non-linear elastic fracture mechanics. This has been made in a cortical bone bonded joint with polymethylmethacrylate (PMMA). Consistent results have been obtained regarding fracture toughness in a widely used bone-to-bone cement joint in many biomedical applications.

Abstract
Virtual Reality (VR) can infiuence users' perception of a given location through experiences in immersive environments. In the tourism context, the use of this technology is crucial in the promotion of products and destinations by improving the perception of tourism content and generating impactful information. However, it is difficult to find comprehensive reviews of studies on VR in tourism. To overcome such limitation, this study is a desk-based, descriptive and retrospective research that combines bibliometric analysis techniques to 37 papers from the Web of Science and Scopus databases, between 1999 and 2020. We aim to provide an overview of the scientific production in the tourism sector associated with VR, identify empirical infiuences of the conceptual framework and suggest new paths. The results allow us to conclude that the use of VR for promotional purposes in tourism is infrequent. The most recurrent studies present software proposals for VR and reviews about technological concepts, marketing and destination image. There is little empirical evidence about the implications and applications of VR. Therefore, we consider imperative more research that explore the applicability of VR in tourism promotion. © 2022, Universidade de Aveiro. All rights reserved.

Abstract
OpenMP can be used in real-time applications to enhance system performance. However, predictability of OpenMP applications is still a challenge. This paper investigates heuristics for the mapping of OpenMP task graphs in underlying threads, for the development of time-predictable OpenMP programs. These approaches are based on a global scheduling queue, as well as per-thread allocation queues. The proposed method is divided into scheduling and allocation phases. In the former phase, OpenMP task-parts are discovered from OpenMP graph and placed in the scheduling queue. Afterwards, an appropriate allocation queue is selected for each task-part using four heuristic algorithms. In the latter phase, the best task-part is selected from the allocation queue to be allocated to and executed by an idle thread. Preliminary simulation results show that the new method overcomes BFS and WFS in terms of scheduling time and idle time.

Abstract

Abstract
Abstract Multiple COVID-19 diagnosis methods based on information collected from patients have been proposed during the global pandemic crisis, with the aim of providing medical staff with quick diagnosis tools to efficiently plan and manage the limited healthcare resources. In general, these methods have been developed to detect COVID-19 positive cases from a particular combination of reported symptoms, and have been evaluated using datasets extracted from different studies with different characteristics. On the other hand, the University of Maryland, in partnership with Facebook, launched the Global COVID-19 Trends and Impact Survey (UMD-CTIS), the largest health surveillance tool to date that has collected information from 114 countries/territories since April 2020. This survey captured various individual features including gender, age groups, self-reported symptoms, isolation measures, and mental health status, among others. In this paper, we compare the performance of different proposed COVID-19 diagnosis methods using the information collected by UMD-CTIS, for the years 2020 and 2021, in five countries: Brazil, Canada, Germany, Japan, and South Africa. The evaluation of these methods with homogeneous data across countries and years provides a solid and consistent comparison among them.