Abstract

Abstract
Medical data exchange between diverse e-health entities can lead to a better healthcare quality, improving the response time in emergency conditions, and a more accurate control of critical medical events (e.g., national health threats or epidemics). However, exchanging large amount of information between different e-health entities is challenging in terms of security, privacy, and network loads, especially for large-scale healthcare systems. Indeed, recent solutions suffer from poor scalability, computational cost, and slow response. Thus, this article proposes medical-edge-blockchain (MEdge-Chain), a holistic framework that exploits the integration of edge computing and blockchain-based technologies to process large amounts of medical data. Specifically, the proposed framework describes a healthcare system that aims to aggregate diverse health entities in a unique national healthcare system by enabling swift, secure exchange, and storage of medical data. Moreover, we design an automated patients monitoring scheme, at the edge, which enables the remote monitoring and efficient discovery of critical medical events. Then, we integrate this scheme with a blockchain architecture to optimize medical data exchanging between diverse entities. Furthermore, we develop a blockchain-based optimization model that aims to optimize the latency and computational cost of medical data exchange between different health entities, hence providing effective and secure healthcare services. Finally, we show the effectiveness of our system in adapting to different critical events, while highlighting the benefits of the proposed intelligent health system.

Abstract
Authoring 360 multisensory videos is a true challenge as the authoring tools available are scarce and restrictive. In this paper, we propose an authoring tool with three different authoring interfaces (desktop, immersive, and tangible interface) for creating multisensory 360 videos with the advantage of having a live preview of the multisensory content that is being produced. An evaluation of the three authoring tools having into account gender, system usability, presence, satisfaction, and effectiveness (time to accomplish tasks, number of errors, and number of help requests) is presented. The sample consisted of 48 participants (24 males and 24 females) evenly distributed between the different interfaces (8 males and 8 females for each interface). The results revealed that gender does not have any impact in the studied interfaces regarding all the dependent variables; immersive and tangible interfaces have higher levels of satisfaction than desktop interface as it allows more interaction freedom, and desktop interface have the lowest time to accomplish the tasks because people are more familiar with keyboard and mouse.

Abstract
Laser scanners are widely used in mobile robotics localization systems but, despite the enormous potential of its use, their high price tag is a major drawback, mainly for hobbyist and educational robotics practitioners that usually have a reduced budget. The Neato XV-11 Laser Scanner is a very low cost alternative, when compared with the current available laser scanners, being this fact the main motivation for its use. The modeling of a hacked Neato XV-11 Laser Scanner allows to provide valuable information that can promote the development of better designs of robot localization systems based on this sensor. This paper presents, as an example, the performance enhancement of a Neato XV-11 Laser Scanner applied to mobile robot self-localization, being used as case study the Perfect Match Algorithm applied to the Robot@Factory competition. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

Abstract
Multi-view has the potential to offer immersive viewing experiences to users, as an alternative to 360 degrees and Virtual Reality (VR) applications. In multi-view, a limited number of camera views are sent to the client and missing views are synthesised locally. Given the substantial complexity associated to view synthesis, considerable attention has been given to optimise the trade-off between bandwidth gains and computing resources, targeting smooth navigation and viewing quality. A still relatively unexplored field is the optimisation of the way navigation interactivity is achieved, i.e. how the user indicates to the system the selection of new viewpoints. In this article, we introduce SmoothMV, a multi-view system that uses a non-intrusive head tracking approach to enhance navigation and Quality of Experience (QoE) of the viewer. It relies on a novel Hot&Cold matrix concept to translate head positioning data into viewing angle selections. Streaming of selected views is done using MPEG-DASH, where a proposed extension to the standard descriptors enables to achieve consistent and flexible view identification.

Abstract
Understanding how acting bridges the emotional bond between spectators and films is essential to depict how humans interact with this rapidly growing digital medium. In recent decades, the research community made promising progress in developing facial expression recognition (FER) methods. However, no emphasis has been put in cinematographic content, which is complex by nature due to the visual techniques used to convey the desired emotions. Our work represents a step towards emotion identification in cinema through facial expressions' analysis. We presented a comprehensive overview of the most relevant datasets used for FER, highlighting problems caused by their heterogeneity and to the inexistence of a universal model of emotions. Built upon this understanding, we evaluated these datasets with a standard image classification models to analyze the feasibility of using facial expressions to determine the emotional charge of a film. To cope with the problem of lack of datasets for the scope under analysis, we demonstrated the feasibility of using a generic dataset for the training process and propose a new way to look at emotions by creating clusters of emotions based on the evidence obtained in the experiments.