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Proceedings, 2020, XoveTIC 2020

3rd XoveTIC Conference

A Coruña, Spain | 8–9 October 2020

Volume Editors: Joaquim de Moura Ramos, Alejandro Puente-Castro, Javier Pereira and Manuel G. Penedo

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Cover Story (view full-size image): This volume gathers papers presented at XOVETIC2020, a conference with the main goal of bringing together young researchers working in big data, artificial intelligence, Internet of Things, HPC [...] Read more.
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Proceedings
A First Approach to Authentication Based on Artificial Intelligence for Touch-Screen Devices
Proceedings 2020, 54(1), 1; https://doi.org/10.3390/proceedings2020054001 - 18 Aug 2020
Viewed by 741
Abstract
Most authentication schemes follow a classical approach, where the users are authenticated only once at the beginning of their sessions. Therefore, it is not possible to verify the legitimate use of such a session or to detect any usurpation. In order to address [...] Read more.
Most authentication schemes follow a classical approach, where the users are authenticated only once at the beginning of their sessions. Therefore, it is not possible to verify the legitimate use of such a session or to detect any usurpation. In order to address this issue, we propose a second-phase authentication scheme that provides not only continuous user authentication during their sessions, but also in a transparent manner, since no additional or intrusive hardware is required. To this purpose, a novel approach was applied to create specific user profiles by means of different Artificial Intelligence techniques. In this work, we aim to study the feasibility of such an authentication scheme, so that it could be applied to a real time environment in order to verify the identity of the actual user against the legitimate user profile. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Computation of Resonance Modes in Open Cavities with Perfectly Matched Layers
Proceedings 2020, 54(1), 2; https://doi.org/10.3390/proceedings2020054002 - 18 Aug 2020
Viewed by 601
Abstract
During the last decade, several authors have addressed that the Perfectly Matched Layers (PML) technique can be used not only for the computation of the near-field in time-dependent and time-harmonic scattering problems, but also to compute numerically the resonances in open cavities. Despite [...] Read more.
During the last decade, several authors have addressed that the Perfectly Matched Layers (PML) technique can be used not only for the computation of the near-field in time-dependent and time-harmonic scattering problems, but also to compute numerically the resonances in open cavities. Despite such complex resonances are not natural eigen-frequencies of the physical system, the numerical determination of this kind of eigenvalues provides information about the model, what can be used in further applications. The present work will be focused on two main specific goals—firstly, the mathematical analysis of the frequency-dependent highly non-linear eigenvalue problem associated to the computation of resonances with the standard PML technique. Second, the implementation of a robust numerical method to approximate resonances in open cavities. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
SARDAM: Service Assistant Robot for Daily Activity Monitoring
Proceedings 2020, 54(1), 3; https://doi.org/10.3390/proceedings2020054003 - 18 Aug 2020
Cited by 1 | Viewed by 515
Abstract
In this work, we propose an autonomous monitoring system for the daily routine of an elderly person. SARDAM (Service Assistant Robot for Daily Activity Monitoring), which is the name of this system, uses a humanoid robot as a key element that carries out [...] Read more.
In this work, we propose an autonomous monitoring system for the daily routine of an elderly person. SARDAM (Service Assistant Robot for Daily Activity Monitoring), which is the name of this system, uses a humanoid robot as a key element that carries out a direct interaction with the user. The purpose of SARDAM is to keep the user active as long as possible by suggesting, and monitoring, a series of daily tasks and healthy habits according to the prescription of a health professional, in order to reduce the early appearance of cognitive and motor impairment. In the current version of SARDAM we use the NAO humanoid robot, which performs a natural interaction with the user through vision and speech libraries. To assure the appropriate execution of the user’s daily tasks, a module for emotion detection has been incorporated in order to propose corrective tasks according to the detected emotion. SARDAM was tested in a scenario with a real user, getting successful results and positive opinions from them that encourage further work. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
A Collaborative Augmented Reality Application for Training and Assistance during Shipbuilding Assembly Processes
Proceedings 2020, 54(1), 4; https://doi.org/10.3390/proceedings2020054004 - 18 Aug 2020
Cited by 1 | Viewed by 713
Abstract
This paper presents the development of a novel Microsoft HoloLens collaborative application that allows shipyard operators to interact with a virtual clutch during its assembly in a real Turbine workshop. Such an Augmented Reality (AR) experience acts as a virtual guide while assembling [...] Read more.
This paper presents the development of a novel Microsoft HoloLens collaborative application that allows shipyard operators to interact with a virtual clutch during its assembly in a real Turbine workshop. Such an Augmented Reality (AR) experience acts as a virtual guide while assembling different parts of a ship. In particular, the proposed application allows operators to position the clutch on a real environment and interact with it. The application also provides information about the documentation of each part of the clutch, showing its blueprints and physical measurements. The proposed AR application enables collaborative AR experiences, allowing users to visualize the same content and animations at the same time and interact simultaneously with 3D objects from multiple devices. Furthermore, the application is integrated with an Industrial Internet of Things (IIoT) framework, resulting on an AR-IIoT application that is able to receive and display real-time sensor data on information panels, as well as to trigger actions through actuators by making use of virtual user interfaces. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Implementing a Web Application for W3C WebAuthn Protocol Testing
Proceedings 2020, 54(1), 5; https://doi.org/10.3390/proceedings2020054005 - 18 Aug 2020
Viewed by 638
Abstract
During the last few years, the FIDO Alliance and the W3C have been working on a new standard called WebAuthn that aims to substitute the obsolete password as an authentication method by using physical security keys instead. Due to its recent design, the [...] Read more.
During the last few years, the FIDO Alliance and the W3C have been working on a new standard called WebAuthn that aims to substitute the obsolete password as an authentication method by using physical security keys instead. Due to its recent design, the standard is still changing and so are the needs for protocol testing. This research has driven the development of a web application that supports the standard and gives extensive information to the user. This tool can be used by WebAuthn developers and researchers, helping them to debug concrete use cases with no need for an ad hoc implementation. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Use of Arduino Microcontroller in Education: Creation of “The Musical Stairs”
Proceedings 2020, 54(1), 6; https://doi.org/10.3390/proceedings2020054006 - 18 Aug 2020
Cited by 1 | Viewed by 605
Abstract
In the last few years, the introduction and use of Information and Communication Technology (onwards ICT) in the classroom has been gradually increased, especially in Science, Technology, Engineering, and Mathematics (onwards STEM) areas. However, the use of ICT technology within the music classroom [...] Read more.
In the last few years, the introduction and use of Information and Communication Technology (onwards ICT) in the classroom has been gradually increased, especially in Science, Technology, Engineering, and Mathematics (onwards STEM) areas. However, the use of ICT technology within the music classroom seems to have stalled in most cases, being relegated to making sound recordings and listening to music fragments. Thanks to the rise of the Maker movement, more and more teachers are interested in introducing new types of ICT in the classroom. In our case, we will show how we developed “The Musical Stairs” to teach the musical concept of pitch, through the creation of a project based in Arduino. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Regression Tree Based Explanation for Anomaly Detection Algorithm
Proceedings 2020, 54(1), 7; https://doi.org/10.3390/proceedings2020054007 - 18 Aug 2020
Cited by 1 | Viewed by 603
Abstract
This work presents EADMNC (Explainable Anomaly Detection on Mixed Numerical and Categorical spaces), a novel approach to address explanation using an anomaly detection algorithm, ADMNC, which provides accurate detections on mixed numerical and categorical input spaces. Our improved algorithm leverages the formulation of [...] Read more.
This work presents EADMNC (Explainable Anomaly Detection on Mixed Numerical and Categorical spaces), a novel approach to address explanation using an anomaly detection algorithm, ADMNC, which provides accurate detections on mixed numerical and categorical input spaces. Our improved algorithm leverages the formulation of the ADMNC model to offer pre-hoc explainability based on CART (Classification and Regression Trees). The explanation is presented as a segmentation of the input data into homogeneous groups that can be described with a few variables, offering supervisors novel information for justifications. To prove scalability and interpretability, we list experimental results on real-world large datasets focusing on network intrusion detection domain. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Network Anomaly Detection Using Machine Learning Techniques
Proceedings 2020, 54(1), 8; https://doi.org/10.3390/proceedings2020054008 - 19 Aug 2020
Viewed by 607
Abstract
While traditional network security methods have been proven useful until now, the flexibility of machine learning techniques makes them a solid candidate in the current scene of our networks. In this paper, we assess how well the latter are capable of detecting security [...] Read more.
While traditional network security methods have been proven useful until now, the flexibility of machine learning techniques makes them a solid candidate in the current scene of our networks. In this paper, we assess how well the latter are capable of detecting security threats in a corporative network. To that end, we configure and compare several models to find the one which fits better with our needs. Furthermore, we distribute the computational load and storage so we can handle extensive volumes of data. The algorithms that we use to create our models, Random Forest, Naive Bayes, and Deep Neural Networks (DNN), are both divergent and tested in other papers in order to make our comparison richer. For the distribution phase, we operate with Apache Structured Streaming, PySpark, and MLlib. As for the results, it is relevant to mention that our dataset has been found to be effectively modelable with just a reduced number of features. Finally, given the outcomes obtained, we find this line of research encouraging and, therefore, this approach worth pursuing. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Reflections about Learning Radiology inside the Multi-User Immersive Environment Second Life® during Confinement by Covid-19
Proceedings 2020, 54(1), 9; https://doi.org/10.3390/proceedings2020054009 - 19 Aug 2020
Viewed by 547
Abstract
The multi-user immersive virtual environment Second Life® has been used to teach radiology to third-year medical students during confinement due to the current Covid-19 pandemic. In general, the students, who are digital natives nowadays, have found it easy to adapt to the [...] Read more.
The multi-user immersive virtual environment Second Life® has been used to teach radiology to third-year medical students during confinement due to the current Covid-19 pandemic. In general, the students, who are digital natives nowadays, have found it easy to adapt to the use of the 3D platform. Although there have been some technical limitations, both students and teachers involved have rated the use of Second Life® during the confinement very highly. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Developing Open-Source Roguelike Games for Visually-Impaired Players by Using Low-Complexity NLP Techniques
Proceedings 2020, 54(1), 10; https://doi.org/10.3390/proceedings2020054010 - 19 Aug 2020
Viewed by 561
Abstract
The prominent graphic component of video games greatly limits the accessibility of this type of entertainment by visually impaired users. We make here an overview of the first games developed within an initiative for the development of roguelike games adapted to visually impaired [...] Read more.
The prominent graphic component of video games greatly limits the accessibility of this type of entertainment by visually impaired users. We make here an overview of the first games developed within an initiative for the development of roguelike games adapted to visually impaired players by using Natural Language Processing techniques. Our approach consists of integrating a multilingual module that automatically generates text descriptions of what is happening within the game. The user can then read such descriptions by means of a screen reader. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
On the Effectiveness of Convolutional Autoencoders on Image-Based Personalized Recommender Systems
Proceedings 2020, 54(1), 11; https://doi.org/10.3390/proceedings2020054011 - 19 Aug 2020
Viewed by 515
Abstract
Over the years, the success of recommender systems has become remarkable. Due to the massive arrival of options that a consumer can have at his/her reach, a collaborative environment was generated, where users from all over the world seek and share their opinions [...] Read more.
Over the years, the success of recommender systems has become remarkable. Due to the massive arrival of options that a consumer can have at his/her reach, a collaborative environment was generated, where users from all over the world seek and share their opinions based on all types of products. Specifically, millions of images tagged with users’ tastes are available on the web. Therefore, the application of deep learning techniques to solve these types of tasks has become a key issue, and there is a growing interest in the use of images to solve them, particularly through feature extraction. This work explores the potential of using only images as sources of information for modeling users’ tastes and proposes a method to provide gastronomic recommendations based on them. To achieve this, we focus on the pre-processing and encoding of the images, proposing the use of a pre-trained convolutional autoencoder as feature extractor. We compare our method with the standard approach of using convolutional neural networks and study the effect of applying transfer learning, reflecting how it is better to use only the specific knowledge of the target domain in this case, even if fewer examples are available. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Application of Artificial Neural Networks for the Monitoring of Episodes of High Toxicity by DSP in Mussel Production Areas in Galicia
Proceedings 2020, 54(1), 12; https://doi.org/10.3390/proceedings2020054012 - 19 Aug 2020
Viewed by 710
Abstract
This study seeks to support, through the use of Artificial Neural Networks (ANN), the decision to perform closings after days without sampling in the Vigo estuary. The opening and closing of the mussel production areas are based on the toxicity analysis of this [...] Read more.
This study seeks to support, through the use of Artificial Neural Networks (ANN), the decision to perform closings after days without sampling in the Vigo estuary. The opening and closing of the mussel production areas are based on the toxicity analysis of this bivalve’s meat. Sometimes it is not possible to obtain the necessary data for effective closing. If there is evidence of an increase in toxicity levels, “Precautionary Closings” on mussel extraction is done. A small error in the forecast of the state of the areas could mean serious losses for the mussel industry and a huge risk for public health. Unlike in previous studies, this study aims to manage the state of the mussel production areas, whilst the others focused on predicting the harmful algae blooms. Having achieved test sensitivity values of 67.40% and test accuracy of 83.00%, these results may lead to new research that involves obtaining more accurate models that can be integrated into a support system. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Numerical Simulation of a Nonlinear Problem Arising in Heat Transfer and Magnetostatics
Proceedings 2020, 54(1), 13; https://doi.org/10.3390/proceedings2020054013 - 19 Aug 2020
Viewed by 485
Abstract
We present a numerical model that comprises a nonlinear partial differential equation. We apply an adaptive stabilised mixed finite element method based on an a posteriori error indicator derived for this particular problem. We describe the numerical algorithm and some numerical results. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
European and American Options Valuation by Unsupervised Learning with Artificial Neural Networks
Proceedings 2020, 54(1), 14; https://doi.org/10.3390/proceedings2020054014 - 19 Aug 2020
Viewed by 526
Abstract
Artificial neural networks (ANNs) have recently also been applied to solve partial differential equations (PDEs). In this work, the classical problem of pricing European and American financial options, based on the corresponding PDE formulations, is studied. Instead of using numerical techniques based on [...] Read more.
Artificial neural networks (ANNs) have recently also been applied to solve partial differential equations (PDEs). In this work, the classical problem of pricing European and American financial options, based on the corresponding PDE formulations, is studied. Instead of using numerical techniques based on finite element or difference methods, we address the problem using ANNs in the context of unsupervised learning. As a result, the ANN learns the option values for all possible underlying stock values at future time points, based on the minimization of a suitable loss function. For the European option, we solve the linear Black–Scholes equation, whereas for the American option, we solve the linear complementarity problem formulation. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Digital Image Quality Prediction System
Proceedings 2020, 54(1), 15; https://doi.org/10.3390/proceedings2020054015 - 19 Aug 2020
Viewed by 515
Abstract
“A picture is worth a thousand words.” Based on this well-known adage, we can say that images are important in our society, and increasingly so. Currently, the Internet is the main channel of socialization and marketing, where we seek to communicate in the [...] Read more.
“A picture is worth a thousand words.” Based on this well-known adage, we can say that images are important in our society, and increasingly so. Currently, the Internet is the main channel of socialization and marketing, where we seek to communicate in the most efficient way possible. People receive a large amount of information daily and that is where the need to attract attention with quality content and good presentation arises. Social networks, for example, are becoming more visual every day. Only on Facebook can you see that the success of a publication increases up to 180% if it is accompanied by an image. That is why it is not surprising that platforms such as Pinterest and Instagram have grown so much, and have positioned themselves thanks to their power to communicate with images. In a world where more and more relationships and transactions are made through computer applications, many decisions are made based on the quality, aesthetic value or impact of digital images. In the present work, a quality prediction system for digital images was developed, trained from the quality perception of a group of humans. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Radiology Seminars with Guest Professors in the Virtual Environment Second Life®: Perception of Learners and Teachers
Proceedings 2020, 54(1), 16; https://doi.org/10.3390/proceedings2020054016 - 19 Aug 2020
Viewed by 486
Abstract
Nine professors of radiology from six different cities were invited to give a 1-hour seminar in the virtual world Second Life® to 154 third-year medical students from the University of Málaga. Students and teachers performed a questionnaire about the cognitive load that [...] Read more.
Nine professors of radiology from six different cities were invited to give a 1-hour seminar in the virtual world Second Life® to 154 third-year medical students from the University of Málaga. Students and teachers performed a questionnaire about the cognitive load that implies receiving/teaching seminars inside Second Life@ and several characteristics involving the experience. This experience was considered remarkably enriching by teachers and learners and opens new interesting pathways for educational contact between students and teachers from different universities, with the advantages of reducing costs and travel time. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Preliminary Analysis of a Virtual Inter-University Game to Learn Radiology within the Second Life® Environment
Proceedings 2020, 54(1), 17; https://doi.org/10.3390/proceedings2020054017 - 19 Aug 2020
Viewed by 470
Abstract
A competition-based game, named League of Rays (LOR), designed to learn radiology within the multi-user virtual environment Second Life was adapted for the participation of teams of four students. The game ran from 20 February to 1 April 2020. Forty-one teams from 16 [...] Read more.
A competition-based game, named League of Rays (LOR), designed to learn radiology within the multi-user virtual environment Second Life was adapted for the participation of teams of four students. The game ran from 20 February to 1 April 2020. Forty-one teams from 16 universities initially signed up and 28 teams from 14 universities finished the game. Participants found this activity fun, enjoyable and useful for their training. Some interesting proposals to be included in future editions of the game and interesting comments on the meaning of developing half of the game during the confinement caused by the Covid-19 pandemic were provided from participants. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Introduction to Second Life® As a Virtual Training Environment: Perception of University Teachers
Proceedings 2020, 54(1), 18; https://doi.org/10.3390/proceedings2020054018 - 20 Aug 2020
Viewed by 519
Abstract
In January 2020, two three-hour workshops on an introduction to Second Life® as an online educational platform were held inside a virtual world. The workshops were dedicated to medical university teachers with the main objective being to let them get to know [...] Read more.
In January 2020, two three-hour workshops on an introduction to Second Life® as an online educational platform were held inside a virtual world. The workshops were dedicated to medical university teachers with the main objective being to let them get to know Second Life® and its formative possibilities. The format of this experience was well received by the participants. Everyone who answered the questionnaire agreed that the environment was useful and interesting and that they would repeat a similar experience again. Ten out of 23 participants (43.5%) declared that they were willing to carry out a teaching activity in Second Life®. This kind of action allows for the promotion of other future in-world actions directed to the training of trainers. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Design of a System to Implement Occupational Stress Studies Trough Wearables Devices and Assessment Tests
Proceedings 2020, 54(1), 19; https://doi.org/10.3390/proceedings2020054019 - 20 Aug 2020
Viewed by 634
Abstract
Introduction: Stress at work is a factor that has repercussions on both a personal and health level, as well as on productivity at work. Objective: To establish if the wearables are devices capable of determining the level of labor stress of [...] Read more.
Introduction: Stress at work is a factor that has repercussions on both a personal and health level, as well as on productivity at work. Objective: To establish if the wearables are devices capable of determining the level of labor stress of working people in a research center. Methodology: This pilot study followed up different variables during 6 months on 11 participants of a research center. In the study, wearables Xiaomi MiB and 3 were used, which recorded and continuously monitored the physical activity and sleep of the participants. On the other hand, different specific evaluation tests were used to measure work stress, quality of life and sleep quality. Results: The data obtained from the tests and the wearables show that men feel slightly more stressed and sleep worse than women; however, men spend more time sitting and walking than women. Conclusions: It is considered important to replicate the study in larger and more heterogeneous cohorts. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Virtual Reality Game Analysis for People with Functional Diversity: An Inclusive Perspective
Proceedings 2020, 54(1), 20; https://doi.org/10.3390/proceedings2020054020 - 20 Aug 2020
Viewed by 301
Abstract
Virtual reality (VR) allows us to simulate everyday life environments with realism and in an immersive environment, with the use of the appropriate hardware. People with functional diversity, either because of environmental barriers or because of their reduced mobility, have fewer opportunities to [...] Read more.
Virtual reality (VR) allows us to simulate everyday life environments with realism and in an immersive environment, with the use of the appropriate hardware. People with functional diversity, either because of environmental barriers or because of their reduced mobility, have fewer opportunities to participate in different daily activities or risk situations outdoors. Therefore, VR can be a technological resource for these people to access, try out, and experience different environments and scenarios, offering new participation experiences. Therefore, the aim of this proposal is to analyze the properties and determine the possibilities of the virtual reality applications available on commercial platforms for use in the practice of rehabilitation and intervention aimed at people with functional diversity. This is a transversal, descriptive study that has focused on the analysis of the 40 applications from the STEAM Virtual Reality and VIVE platforms for High Tech Computer Corporation (HTC). After analysis, it has been observed that there are no applications available that are fully accessible and with a minimum degree of usability for use by people with functional diversity. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Design and Implementation of a Physical Bitcoin Coin
Proceedings 2020, 54(1), 21; https://doi.org/10.3390/proceedings2020054021 - 20 Aug 2020
Viewed by 600
Abstract
One of the major factors hindering the adoption of crypto assets in general, and Bitcoin in particular, is the high level of complexity they present to the common user. Although physical coins are a possible solution, the need to place trust in the [...] Read more.
One of the major factors hindering the adoption of crypto assets in general, and Bitcoin in particular, is the high level of complexity they present to the common user. Although physical coins are a possible solution, the need to place trust in the manufacturers (so that they throw away the private key) is a big drawback that has hampered their widespread use. The recent boom of the maker movement has brought in a significant number of users with access to 3D printing devices, as well as the supporting electronic and computing resources. We have taken advantage of these capabilities to develop an open source project that interested parties can use to easily print a physical model of a Bitcoin coin, along with the necessary software that allows the creation and validation of keys and addresses. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
An Agent-Based Model to Simulate the Spread of a Virus Based on Social Behavior and Containment Measures
Proceedings 2020, 54(1), 22; https://doi.org/10.3390/proceedings2020054022 - 20 Aug 2020
Viewed by 488
Abstract
COVID-19 has brought a new normality in society. However, to avoid the situation, the virus must be stopped. There are several ways in which the governments of the world have taken action, from small measures like general cleaning up to large-scale measures like [...] Read more.
COVID-19 has brought a new normality in society. However, to avoid the situation, the virus must be stopped. There are several ways in which the governments of the world have taken action, from small measures like general cleaning up to large-scale measures like confinement. In this work, we present an agent-based tool that allows for simulating the virus expansion as a function of these containment measures and the Social Behavior based on people needs, beliefs, and social relations. Once this tool has been validated, it will be useful to evaluate the impact of future containment measures so that the most balanced ones can be found for the effectiveness of the measures and their good reception by the population. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Shiny Dashboard for Monitoring the COVID-19 Pandemic in Spain
Proceedings 2020, 54(1), 23; https://doi.org/10.3390/proceedings2020054023 - 20 Aug 2020
Cited by 1 | Viewed by 972
Abstract
Real-time monitoring of events such as the recent pandemic caused by COVID-19, as well as the visualization of the effects produced by its expansion, has highlighted the need to join forces in fields already widely used to working hand in hand, such as [...] Read more.
Real-time monitoring of events such as the recent pandemic caused by COVID-19, as well as the visualization of the effects produced by its expansion, has highlighted the need to join forces in fields already widely used to working hand in hand, such as medicine, biology and information technology. Our dashboard is developed in R and is supported by the Shiny package to generate an attractive visualization tool: COVID-19 Spain automatically produces daily updates from official sources (Carlos III Research Institute and Ministry of Health, Consumer Affairs and Welfare) in cases, deaths, recovered, ICU admissions and accumulated daily incidence. In addition, it shows on a georeferenced map the evolution of active, new and accumulated cases by autonomous community allowing to travel in time from the origin to the last available day, which allows to visualize the expansion of infections and serves as a visual support for epidemiological studies. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Decentralized P2P Broker for M2M and IoT Applications
Proceedings 2020, 54(1), 24; https://doi.org/10.3390/proceedings2020054024 - 20 Aug 2020
Viewed by 531
Abstract
The recent increase in the number of connected IoT devices, as well as the heterogeneity of the environments where they are deployed, has derived into the growth of the complexity of Machine-to-Machine (M2M) communication protocols and technologies. In addition, the hardware used by [...] Read more.
The recent increase in the number of connected IoT devices, as well as the heterogeneity of the environments where they are deployed, has derived into the growth of the complexity of Machine-to-Machine (M2M) communication protocols and technologies. In addition, the hardware used by IoT devices has become more powerful and efficient. Such enhancements have made it possible to implement novel decentralized computing architectures like the ones based on edge computing, which offload part of the central server processing by using multiple distributed low-power nodes. In order to ease the deployment and synchronization of decentralized edge computing nodes, this paper describes an M2M distributed protocol based on Peer-to-Peer (P2P) communications that can be executed on low-power ARM devices. In addition, this paper proposes to make use of brokerless communications by using a distributed publication/subscription protocol. Thanks to the fact that information is stored in a distributed way among the nodes of the swarm and since each node can implement a specific access control system, the proposed system is able to make use of write access mechanisms and encryption for the stored data so that the rest of the nodes cannot access sensitive information. In order to test the feasibility of the proposed approach, a comparison with an Message-Queuing Telemetry Transport (MQTT) based architecture is performed in terms of latency, network consumption and performance. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Joint Optic Disc and Cup Segmentation Using Self-Supervised Multimodal Reconstruction Pre-Training
Proceedings 2020, 54(1), 25; https://doi.org/10.3390/proceedings2020054025 - 20 Aug 2020
Viewed by 480
Abstract
The analysis of the optic disc and cup in retinal images is important for the early diagnosis of glaucoma. In order to improve the joint segmentation of these relevant retinal structures, we propose a novel approach applying the self-supervised multimodal reconstruction of retinal [...] Read more.
The analysis of the optic disc and cup in retinal images is important for the early diagnosis of glaucoma. In order to improve the joint segmentation of these relevant retinal structures, we propose a novel approach applying the self-supervised multimodal reconstruction of retinal images as pre-training for deep neural networks. The proposed approach is evaluated on different public datasets. The obtained results indicate that the self-supervised multimodal reconstruction pre-training improves the performance of the segmentation. Thus, the proposed approach presents a great potential for also improving the interpretable diagnosis of glaucoma. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Analysis and Definition of Data Flows Generated by Bio Stimuli in the Design of Interactive Immersive Environments
Proceedings 2020, 54(1), 26; https://doi.org/10.3390/proceedings2020054026 - 20 Aug 2020
Cited by 1 | Viewed by 759
Abstract
This work focuses on interactivity as one of the essential factors for creating immersive environments, particularly interactivity that generates involuntary responses over which the user does not have conscious control. A dynamic and adaptive model was designed to analyze and define the data [...] Read more.
This work focuses on interactivity as one of the essential factors for creating immersive environments, particularly interactivity that generates involuntary responses over which the user does not have conscious control. A dynamic and adaptive model was designed to analyze and define the data flow generated by bio stimuli for the design of interactive immersive environments. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
CultUnity3D: A Virtual Spatial Ecosystem for Digital Engagement with Cultural Heritage Sites
Proceedings 2020, 54(1), 27; https://doi.org/10.3390/proceedings2020054027 - 20 Aug 2020
Viewed by 474
Abstract
In order to help enhance public outreach and understanding of historical sites, we developed a virtual spatial ecosystem called CultUnity3D. It consists of a set of components specifically implemented within the Unity engine that enable the user to virtually explore spatial changes over [...] Read more.
In order to help enhance public outreach and understanding of historical sites, we developed a virtual spatial ecosystem called CultUnity3D. It consists of a set of components specifically implemented within the Unity engine that enable the user to virtually explore spatial changes over time in two different modes, and to learn about the past of a built environment through the integration of and interaction with research sources and narrative. Although we built CultUnity3D for a particular case study, which is the monastic site of San Julián de Samos (Spain), this in-progress virtual ecosystem has been thought out and designed for continued and reusable development. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Web Server and R Library for the Calculation of Markov Chains Molecular Descriptors
Proceedings 2020, 54(1), 28; https://doi.org/10.3390/proceedings2020054028 - 20 Aug 2020
Viewed by 419
Abstract
Markov Chain Molecular Descriptors (MCDs) have been largely used to solve Cheminformatics problems. The software to perform the calculation is not always available for general users. In this work, we developed the first library in R for the calculation of MCDs and we [...] Read more.
Markov Chain Molecular Descriptors (MCDs) have been largely used to solve Cheminformatics problems. The software to perform the calculation is not always available for general users. In this work, we developed the first library in R for the calculation of MCDs and we also report the first public web server for the calculation of MCDs online that include the calculation of a new class of MCDs called Markov Singular values. We also report the first Cheminformatics study of the biological activity of 5644 compounds against colorectal cancer. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Validation of Self-Quantification Xiaomi Band in a Clinical Sleep Unit
Proceedings 2020, 54(1), 29; https://doi.org/10.3390/proceedings2020054029 - 21 Aug 2020
Viewed by 785
Abstract
Polysomnography (PSG) is currently the accepted gold standard for sleep studies, as it measures multiple variables that lead to a clear diagnosis of any sleep disorder. However, it has some clear drawbacks, since it can only be performed by qualified technicians, has a [...] Read more.
Polysomnography (PSG) is currently the accepted gold standard for sleep studies, as it measures multiple variables that lead to a clear diagnosis of any sleep disorder. However, it has some clear drawbacks, since it can only be performed by qualified technicians, has a high cost and complexity and is very invasive. In the last years, actigraphy has been used along PSG for sleep studies. In this study, we intend to assess the capability of the new Xiaomi Mi Smart Band 5 to be used as an actigraphy tool. Sleep measures from PSG and Xiaomi Mi Smart Band 5 recorded in the same night will be obtained and further analysed to assess their concordance. For this analysis, we perform a paired sample t-test to compare the different measures, Bland–Altman plots to evaluate the level of agreement between the Mi Band and PSG and Epoch by Epoch analysis to study the ability of the Mi Band to correctly identify PSG-defined sleep stages. This study belongs to the research field known as participatory health, which aims to offer an innovative healthcare model driven by the patients themselves, leading to civic empowerment and self-management of health. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Designing an Open Source Virtual Assistant
Proceedings 2020, 54(1), 30; https://doi.org/10.3390/proceedings2020054030 - 21 Aug 2020
Viewed by 594
Abstract
A chatbot is a type of agent that allows people to interact with an information repository using natural language. Nowadays, chatbots have been incorporated in the form of conversational assistants on the most important mobile and desktop platforms. In this article, we present [...] Read more.
A chatbot is a type of agent that allows people to interact with an information repository using natural language. Nowadays, chatbots have been incorporated in the form of conversational assistants on the most important mobile and desktop platforms. In this article, we present our design of an assistant developed with open-source and widely used components. Our proposal covers the process end-to-end, from information gathering and processing to visual and speech-based interaction. We have deployed a proof of concept over the website of our Computer Science Faculty. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Analysis of Separability of COVID-19 and Pneumonia in Chest X-ray Images by Means of Convolutional Neural Networks
Proceedings 2020, 54(1), 31; https://doi.org/10.3390/proceedings2020054031 - 21 Aug 2020
Viewed by 545
Abstract
The new coronavirus (COVID-19) is a disease that is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). On 11 March 2020, the coronavirus outbreak has been labelled a global pandemic by the World Health Organization. In this context, chest X-ray imaging has [...] Read more.
The new coronavirus (COVID-19) is a disease that is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). On 11 March 2020, the coronavirus outbreak has been labelled a global pandemic by the World Health Organization. In this context, chest X-ray imaging has become a remarkably powerful tool for the identification of patients with COVID-19 infections at an early stage when clinical symptoms may be unspecific or sparse. In this work, we propose a complete analysis of separability of COVID-19 and pneumonia in chest X-ray images by means of Convolutional Neural Networks. Satisfactory results were obtained that demonstrated the suitability of the proposed system, improving the efficiency of the medical screening process in the healthcare systems. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Fully Automatic Retinal Vascular Tortuosity Assessment Integrating Domain-Related Information
Proceedings 2020, 54(1), 32; https://doi.org/10.3390/proceedings2020054032 - 21 Aug 2020
Viewed by 487
Abstract
The fundus of the eye is the only part of the human body that allows a direct non-invasive observation of the circulatory system. Retinal vascular tortuosity presents a valuable potential for diagnostic and treatment purposes of relevant vascular and systemic diseases. This work [...] Read more.
The fundus of the eye is the only part of the human body that allows a direct non-invasive observation of the circulatory system. Retinal vascular tortuosity presents a valuable potential for diagnostic and treatment purposes of relevant vascular and systemic diseases. This work presents a computational metric for the tortuosity characterization that combines mathematical representations of the vessel segments with anatomical properties of the fundus image such as the vessel caliber, the distance to the optic disc, the distance to the fovea and the distinction between arteries and veins. The evaluation of the prognostic performance shows that the incorporation of the domain-related information allows a reliable characterization of the retinal vascular tortuosity that provides a better representation of the expert perception. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Data Extraction in Insurance Photo-Inspections Using Computer Vision
Proceedings 2020, 54(1), 33; https://doi.org/10.3390/proceedings2020054033 - 21 Aug 2020
Viewed by 513
Abstract
Recent advances in computer vision and artificial intelligence allow for a better processing of complex information in many fields of human activity. One such field is vehicle expertise and inspection. This paper presents the development of systems for the automatic reading of French [...] Read more.
Recent advances in computer vision and artificial intelligence allow for a better processing of complex information in many fields of human activity. One such field is vehicle expertise and inspection. This paper presents the development of systems for the automatic reading of French and Spanish license plates, as well as odometer value reading in dashboard photographs. These were trained and validated with real examples of more than 4000 vehicles, while addressing typical problems with irregular data acquisition. The systems proposed have found use in a real environment and are employed as assistance in vehicle appraisal. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Probiotic: First Prescriptive Application of Probiotics in Spain
Proceedings 2020, 54(1), 34; https://doi.org/10.3390/proceedings2020054034 - 21 Aug 2020
Viewed by 527
Abstract
The study of the intestinal microbiota is one of the greatest challenges in today’s clinical environment. Thus, probiotics have been established as a focus for its stability, as they play a key role in its regulation. The development of an automated technique that [...] Read more.
The study of the intestinal microbiota is one of the greatest challenges in today’s clinical environment. Thus, probiotics have been established as a focus for its stability, as they play a key role in its regulation. The development of an automated technique that allows the practitioners the smooth search for the optimal probiotic is postulated as the main objective of this study. Despite the existence of previous attempts at applications for this purpose, they have only been carried out for the countries of origin, preventing them from being used in others such as Spain. Therefore, a system has been developed with open, multi-platform, and free technologies, which manages to locate the optimal probiotic for each pathology. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Deep Image Segmentation for Breast Keypoint Detection
Proceedings 2020, 54(1), 35; https://doi.org/10.3390/proceedings2020054035 - 21 Aug 2020
Viewed by 586
Abstract
The main aim of breast cancer conservative treatment is the optimisation of the aesthetic outcome and, implicitly, women’s quality of life, without jeopardising local cancer control and overall survival. Moreover, there has been an effort to try to define an optimal tool capable [...] Read more.
The main aim of breast cancer conservative treatment is the optimisation of the aesthetic outcome and, implicitly, women’s quality of life, without jeopardising local cancer control and overall survival. Moreover, there has been an effort to try to define an optimal tool capable of performing the aesthetic evaluation of breast cancer conservative treatment outcomes. Recently, a deep learning algorithm that integrates the learning of keypoints’ probability maps in the loss function as a regularisation term for the robust learning of the keypoint localisation has been proposed. However, it achieves the best results when used in cooperation with a shortest-path algorithm that models images as graphs. In this work, we analysed a novel algorithm based on the interaction of deep image segmentation and deep keypoint detection models capable of improving both state-of-the-art performance and execution-time on the breast keypoint detection task. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
An Intelligent and Collaborative Multiagent System in a 3D Environment
Proceedings 2020, 54(1), 36; https://doi.org/10.3390/proceedings2020054036 - 21 Aug 2020
Viewed by 569
Abstract
Multiagent systems (MASs) allow facing complex, heterogeneous, distributed problems difficult to solve by only one software agent. The world of video games provides problems and suitable environments for the use of MAS. In the field of games, Unity is one of the most [...] Read more.
Multiagent systems (MASs) allow facing complex, heterogeneous, distributed problems difficult to solve by only one software agent. The world of video games provides problems and suitable environments for the use of MAS. In the field of games, Unity is one of the most used engines and allows the development of intelligent agents in virtual environments. However, although Unity allows working in multiagent environments, it does not provide functionalities to facilitate the development of MAS. The aim of this work is to create a multiagent system in Unity. For this purpose, a predator–prey problem was designed in which the agents must cooperate to arrest a thief driven by a human player. To solve this cooperative problem, it is required to create the representation of the environment and the agents in 3D; to equip the agents with vision, contact, and sound sensors to perceive the environment; to implement the agents’ behaviors; and, finally but not less important, to build a communication system between agents that allows negotiation, collaboration, and cooperation between them to create a complex, role-based chasing strategy. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Comparison of Image Compressions: Analog Transformations
Proceedings 2020, 54(1), 37; https://doi.org/10.3390/proceedings2020054037 - 21 Aug 2020
Viewed by 402
Abstract
A comparison between the four most used transforms, the discrete Fourier transform (DFT), discrete cosine transform (DCT), the Walsh–Hadamard transform (WHT) and the Haar-wavelet transform (DWT), for the transmission of analog images, varying their compression and comparing their quality, is presented. Additionally, performance [...] Read more.
A comparison between the four most used transforms, the discrete Fourier transform (DFT), discrete cosine transform (DCT), the Walsh–Hadamard transform (WHT) and the Haar-wavelet transform (DWT), for the transmission of analog images, varying their compression and comparing their quality, is presented. Additionally, performance tests are done for different levels of white Gaussian additive noise. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Adaptive Real-Time Method for Anomaly Detection Using Machine Learning
Proceedings 2020, 54(1), 38; https://doi.org/10.3390/proceedings2020054038 - 22 Aug 2020
Viewed by 826
Abstract
Anomaly detection is a sub-area of machine learning that deals with the development of methods to distinguish among normal and anomalous data. Due to the frequent use of anomaly-detection systems in monitoring and the lack of methods capable of learning in real time, [...] Read more.
Anomaly detection is a sub-area of machine learning that deals with the development of methods to distinguish among normal and anomalous data. Due to the frequent use of anomaly-detection systems in monitoring and the lack of methods capable of learning in real time, this research presents a new method that provides such online adaptability. The method bases its operation on the properties of scaled convex hulls. It begins building a convex hull, using a minimum set of data, that is adapted and subdivided along time to accurately fit the boundary of the normal class data. The model has online learning ability and its execution can be carried out in a distributed and parallel way, all of them interesting advantages when dealing with big datasets. The method has been compared to other state-of-the-art algorithms demonstrating its effectiveness. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Numerical Model of a 28-GHz Frequency Diverse Array Antenna
Proceedings 2020, 54(1), 39; https://doi.org/10.3390/proceedings2020054039 - 22 Aug 2020
Viewed by 566
Abstract
In this work we make use of the frequency diverse array (FDA) concept, whose design is based upon a frequency increment across the antenna elements to generate a beam steering that is a function of angle, time and range. For a possible use [...] Read more.
In this work we make use of the frequency diverse array (FDA) concept, whose design is based upon a frequency increment across the antenna elements to generate a beam steering that is a function of angle, time and range. For a possible use of this technique in 5G detection systems, a 28-GHz FDA numerical model, designed with help of a software tool, is analyzed. Some practical conclusions are drawn from the presented results. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Feature Selection in Big Image Datasets
Proceedings 2020, 54(1), 40; https://doi.org/10.3390/proceedings2020054040 - 24 Aug 2020
Viewed by 522
Abstract
In computer vision, current feature extraction techniques generate high dimensional data. Both convolutional neural networks and traditional approaches like keypoint detectors are used as extractors of high-level features. However, the resulting datasets have grown in the number of features, leading into long training [...] Read more.
In computer vision, current feature extraction techniques generate high dimensional data. Both convolutional neural networks and traditional approaches like keypoint detectors are used as extractors of high-level features. However, the resulting datasets have grown in the number of features, leading into long training times due to the curse of dimensionality. In this research, some feature selection methods were applied to these image features through big data technologies. Additionally, we analyzed how image resolutions may affect to extracted features and the impact of applying a selection of the most relevant features. Experimental results show that making an important reduction of the extracted features provides classification results similar to those obtained with the full set of features and, in some cases, outperforms the results achieved using broad feature vectors. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Developing an Open-Source, Low-Cost, Radon Monitoring System
Proceedings 2020, 54(1), 41; https://doi.org/10.3390/proceedings2020054041 - 24 Aug 2020
Cited by 1 | Viewed by 435
Abstract
The United States Environmental Protection Agency (USEPA) and the International Agency for Research on Cancer (IARC) have declared Radon gas a human carcinogen. Spain has several regions with high radon concentrations, Galicia (northwestern Spain) being one with the highest Radon concentration. In this [...] Read more.
The United States Environmental Protection Agency (USEPA) and the International Agency for Research on Cancer (IARC) have declared Radon gas a human carcinogen. Spain has several regions with high radon concentrations, Galicia (northwestern Spain) being one with the highest Radon concentration. In this work, we present the development of an open-source and low-cost radon monitoring and alert system. The system has two parts: devices and the backend. The devices integrate a Radon sensor, capable of measuring Radon levels every 10 min, and several environmental sensors capable of measuring temperature, humidity, atmospheric pressure, and air pollution. The devices send all the information to the backend, which stores it, exposes it in a web interface, and uses the historical data to predict the radon levels for the following hours. If the radon levels are predicted to overpass the threshold in the next hour, the system issues an alert via several channels (email and MQTT) to the configured recipients for the corresponding device, allowing them to take measures to lower the Radon concentration. The results of this work indicate that the system allows the radon levels to be greatly reduced and makes the development of a low cost and open-source radon monitoring system feasible. The system scalability allows a network of sensors to be created that can help mitigate the health hazard that high radon concentrations create. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Application of Adaptive Virtual Environments Through Biofeedback for the Treatment of Phobias
Proceedings 2020, 54(1), 42; https://doi.org/10.3390/proceedings2020054042 - 25 Aug 2020
Viewed by 610
Abstract
This study proposes solutions to help people with phobias through the use of virtual environments that allow a contact between the subjects and these phobias. Using neurofeedback, the systems, depending on the emotional state of the user, adapt the scenarios allowing more or [...] Read more.
This study proposes solutions to help people with phobias through the use of virtual environments that allow a contact between the subjects and these phobias. Using neurofeedback, the systems, depending on the emotional state of the user, adapt the scenarios allowing more or less intensity. The phobias these systems treat are social phobia, entomophobia and claustrophobia. The solutions have been developed using Unity, Muse 2 and Vive HTC. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
The Use of Portable EEG Devices in Development of Immersive Virtual Reality Environments for Converting Emotional States into Specific Commands
Proceedings 2020, 54(1), 43; https://doi.org/10.3390/proceedings2020054043 - 25 Aug 2020
Cited by 1 | Viewed by 642
Abstract
The application of electroencephalography electrodes in Virtual Reality (VR) glasses allows users to relate cognitive, emotional, and social functions with the exposure to certain stimuli. The development of non-invasive portable devices, coupled with VR, allows for the collection of electroencephalographic data. One of [...] Read more.
The application of electroencephalography electrodes in Virtual Reality (VR) glasses allows users to relate cognitive, emotional, and social functions with the exposure to certain stimuli. The development of non-invasive portable devices, coupled with VR, allows for the collection of electroencephalographic data. One of the devices that embraced this new trend is Looxid LinkTM, a system that adds electroencephalography to HTC VIVETM, VIVE ProTM, VIVE Pro EyeTM, or Oculus Rift STM glasses to create interactive environments using brain signals. This work analyzes the possibility of using the Looxid LinkTM device to perceive, evaluate and monitor the emotions of users exposed to VR. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Enhancing Retinal Blood Vessel Segmentation through Self-Supervised Pre-Training
Proceedings 2020, 54(1), 44; https://doi.org/10.3390/proceedings2020054044 - 25 Aug 2020
Viewed by 501
Abstract
The segmentation of the retinal vasculature is fundamental in the study of many diseases. However, its manual completion is problematic, which motivates the research on automatic methods. Nowadays, these methods usually employ Fully Convolutional Networks (FCNs), whose success is highly conditioned by the [...] Read more.
The segmentation of the retinal vasculature is fundamental in the study of many diseases. However, its manual completion is problematic, which motivates the research on automatic methods. Nowadays, these methods usually employ Fully Convolutional Networks (FCNs), whose success is highly conditioned by the network architecture and the availability of many annotated data, something infrequent in medicine. In this work, we present a novel application of self-supervised multimodal pre-training to enhance the retinal vasculature segmentation. The experiments with diverse FCN architectures demonstrate that, independently of the architecture, this pre-training allows one to overcome annotated data scarcity and leads to significantly better results with less training on the target task. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Study on Relevant Features in COVID-19 PCR Tests
Proceedings 2020, 54(1), 45; https://doi.org/10.3390/proceedings2020054045 - 26 Aug 2020
Viewed by 551
Abstract
In the year 2020, the world suffered the effects of a global pandemic. COVID-19 is a disease that mainly affects the respiratory system of patients, even causing a disproportionate response of the immune system and further spreading the damage to other vital organs. [...] Read more.
In the year 2020, the world suffered the effects of a global pandemic. COVID-19 is a disease that mainly affects the respiratory system of patients, even causing a disproportionate response of the immune system and further spreading the damage to other vital organs. The main means by which health care services detected this viral disease was through the use of Polymerase Chain Reactions (PCRs). These PCRs allow the detection of known chains of the genetic code of the virus in samples of sputum. In this work, we study PCR signal features that allow to automatize the analysis of hundreds of PCRs. The findings obtained from the study have shown these features to be capable of obtaining successful results in the detection of COVID-19 in PCR samples, with only a small fraction of the information extracted by the clinicians for that purpose. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Mobile Application for Analysing the Development of Motor Skills in Children
Proceedings 2020, 54(1), 46; https://doi.org/10.3390/proceedings2020054046 - 26 Aug 2020
Cited by 1 | Viewed by 695
Abstract
This work presents a mobile application to complement and reinforce the specific physical activities in children through training prior to such activities and monitoring their progress after it. This experiment has been developed on a healthy population of children from an education centre [...] Read more.
This work presents a mobile application to complement and reinforce the specific physical activities in children through training prior to such activities and monitoring their progress after it. This experiment has been developed on a healthy population of children from an education centre in the area of A Coruña. The results show increasing errors for lower primary school years, as expected, and also strongly dependent on the motor path type or characteristic. Therefore, this tool will be suitable for use with children affected by motor coordination difficulties. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
A-Frame as a Tool to Create Artistic Collective Installations in Virtual Reality
Proceedings 2020, 54(1), 47; https://doi.org/10.3390/proceedings2020054047 - 26 Aug 2020
Viewed by 504
Abstract
Virtual Reality, due to its complexity and technological requirements, has a set of frictions that hinder its dissemination. The main ones can be summarized in the requirement to learn complex developing environments, like game engines, then we need to install applications, specific to [...] Read more.
Virtual Reality, due to its complexity and technological requirements, has a set of frictions that hinder its dissemination. The main ones can be summarized in the requirement to learn complex developing environments, like game engines, then we need to install applications, specific to each operating system and according to the means through which they can be accessed. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Artificial Intelligence in Pre-University Education: What and How to Teach
Proceedings 2020, 54(1), 48; https://doi.org/10.3390/proceedings2020054048 - 26 Aug 2020
Viewed by 508
Abstract
The present paper is part of the European Erasmus+ project on educational innovation led by the UDC and entitled “AI+: Developing an Artificial Intelligence Curriculum adapted to European High School”. In this paper, the progress achieved during the first year of the project [...] Read more.
The present paper is part of the European Erasmus+ project on educational innovation led by the UDC and entitled “AI+: Developing an Artificial Intelligence Curriculum adapted to European High School”. In this paper, the progress achieved during the first year of the project will be presented. Mainly, the definition of the methodological approach for this future subject has been defined, and the AI topics to be dealt with at this age have been established. It has been a great effort to select the most appropriate focus for this subject considering the students’ and teachers’ technical background and the schools’ equipment. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Development of an Open Source Tool and a Multi-Platform for Generation of Forensic Reports
Proceedings 2020, 54(1), 49; https://doi.org/10.3390/proceedings2020054049 - 27 Aug 2020
Viewed by 472
Abstract
Computer Forensics is a science that is part of computer security and focuses on identifying, preserving, analyzing and presenting electronic evidence that has been found on a device. This process has to be thoroughly documented by the expert who carries it out, and [...] Read more.
Computer Forensics is a science that is part of computer security and focuses on identifying, preserving, analyzing and presenting electronic evidence that has been found on a device. This process has to be thoroughly documented by the expert who carries it out, and must be adapted to standards such as UNE 197010:2015 or ISO/IEC 27042:2015. However, there are no tools to facilitate this task. Therefore, in this work, a multiplatform and open source tool is developed to facilitate the expert’s elaboration of the report, and the management of the documentation related to the case, while keeping this information safe. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Identification of Prevotella, Anaerotruncus and Eubacterium Genera by Machine Learning Analysis of Metagenomic Profiles for Stratification of Patients Affected by Type I Diabetes
Proceedings 2020, 54(1), 50; https://doi.org/10.3390/proceedings2020054050 - 27 Aug 2020
Viewed by 560
Abstract
Previous works have reported different bacterial strains and genera as the cause of different clinical pathological conditions. In our approach, using the fecal metagenomic profiles of newborns, a machine learning-based model was generated capable of discerning between patients affected by type I diabetes [...] Read more.
Previous works have reported different bacterial strains and genera as the cause of different clinical pathological conditions. In our approach, using the fecal metagenomic profiles of newborns, a machine learning-based model was generated capable of discerning between patients affected by type I diabetes and controls. Furthermore, a random forest algorithm achieved a 0.915 in AUROC. The automation of processes and support to clinical decision making under metagenomic variables of interest may result in lower experimental costs in the diagnosis of complex diseases of high prevalence worldwide. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
aspBEEF: Explaining Predictions Through Optimal Clustering
Proceedings 2020, 54(1), 51; https://doi.org/10.3390/proceedings2020054051 - 28 Aug 2020
Viewed by 531
Abstract
In this paper we introduce aspBEEF, a tool for generating explanations for the outcome of an arbitrary machine learning classifier. This is done using Grover’s et al. framework known as Balanced English Explanations of Forecasts (BEEF) that generates explanations in terms of in [...] Read more.
In this paper we introduce aspBEEF, a tool for generating explanations for the outcome of an arbitrary machine learning classifier. This is done using Grover’s et al. framework known as Balanced English Explanations of Forecasts (BEEF) that generates explanations in terms of in terms of finite intervals over the values of the input features. Since the problem of obtaining an optimal BEEF explanation has been proved to be NP-complete, BEEF existing implementation computes an approximation. In this work we use instead an encoding into the Answer Set Programming paradigm, specialized in solving NP problems, to guarantee that the computed solutions are optimal. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Mining of the Milky Way Star Archive Gaia-DR2. Searching for Binary Stars in Planetary Nebulae
Proceedings 2020, 54(1), 52; https://doi.org/10.3390/proceedings2020054052 - 31 Aug 2020
Viewed by 503
Abstract
The aim of this work is to search for binary stars associated to planetary nebulae (ionized stellar envelopes in expansion), by mining the astronomical archive of Gaia DR2, that is composed by around 1.7 billion stellar sources. For this task, we selected those [...] Read more.
The aim of this work is to search for binary stars associated to planetary nebulae (ionized stellar envelopes in expansion), by mining the astronomical archive of Gaia DR2, that is composed by around 1.7 billion stellar sources. For this task, we selected those objects with coincident astrometric parameters (parallaxes and proper motions) with the corresponding central star, among a sample of 211 planetary nebulae. By this method, we found eight binary systems, and we obtained their components positions, separations, temperatures and luminosities, as well as some of their masses and ages. In addition, we estimated the probability for each companion star of having been detected by chance and we analyzed how the number of false matches increase as the separation distance between both stars gets larger. All these procedures have been carried out making use of data mining techniques. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Study of Machine Learning Techniques for EEG Eye State Detection
Proceedings 2020, 54(1), 53; https://doi.org/10.3390/proceedings2020054053 - 31 Aug 2020
Viewed by 619
Abstract
A comparison of different machine learning techniques for eye state identification through Electroencephalography (EEG) signals is presented in this paper. (1) Background: We extend our previous work by studying several techniques for the extraction of the features corresponding to the mental states of [...] Read more.
A comparison of different machine learning techniques for eye state identification through Electroencephalography (EEG) signals is presented in this paper. (1) Background: We extend our previous work by studying several techniques for the extraction of the features corresponding to the mental states of open and closed eyes and their subsequent classification; (2) Methods: A prototype developed by the authors is used to capture the brain signals. We consider the Discrete Fourier Transform (DFT) and the Discrete Wavelet Transform (DWT) for feature extraction; Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) for state classification; and Independent Component Analysis (ICA) for preprocessing the data; (3) Results: The results obtained from some subjects show the good performance of the proposed methods; and (4) Conclusion: The combination of several techniques allows us to obtain a high accuracy of eye identification. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Acceleration of a Feature Selection Algorithm Using High Performance Computing
Proceedings 2020, 54(1), 54; https://doi.org/10.3390/proceedings2020054054 - 01 Sep 2020
Viewed by 685
Abstract
Feature selection is a subfield of data analysis that is on reducing the dimensionality of datasets, so that subsequent analyses over them can be performed in affordable execution times while keeping the same results. Joint Mutual Information (JMI) is a highly used feature [...] Read more.
Feature selection is a subfield of data analysis that is on reducing the dimensionality of datasets, so that subsequent analyses over them can be performed in affordable execution times while keeping the same results. Joint Mutual Information (JMI) is a highly used feature selection method that removes irrelevant and redundant characteristics. Nevertheless, it has high computational complexity. In this work, we present a multithreaded MPI parallel implementation of JMI to accelerate its execution on distributed memory systems, reaching speedups of up to 198.60 when running on 256 cores, and allowing for the analysis of very large datasets that do not fit in the main memory of a single node. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
A Doubly Smoothed PD Estimator in Credit Risk
Proceedings 2020, 54(1), 55; https://doi.org/10.3390/proceedings2020054055 - 01 Sep 2020
Viewed by 520
Abstract
In this work a doubly smoothed probability of default (PD) estimator is proposed based on a smoothed version of the survival Beran’s estimator. The asymptotic properties of both the smoothed survival and PD estimators are proved and their behaviour is analyzed by simulation. [...] Read more.
In this work a doubly smoothed probability of default (PD) estimator is proposed based on a smoothed version of the survival Beran’s estimator. The asymptotic properties of both the smoothed survival and PD estimators are proved and their behaviour is analyzed by simulation. The results allow us to conclude that the time variable smoothing reduce the error committed in the PD estimation. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Open Source Monitoring System for IT Infrastructures Incorporating IoT-Based Sensors
Proceedings 2020, 54(1), 56; https://doi.org/10.3390/proceedings2020054056 - 03 Sep 2020
Viewed by 492
Abstract
This paper introduces the development of a data center monitoring system based on IoT technologies. The system is meant to work as an administrative tool for system administrators in any environment, but mainly focused on data centers, since it integrates sensor and server [...] Read more.
This paper introduces the development of a data center monitoring system based on IoT technologies. The system is meant to work as an administrative tool for system administrators in any environment, but mainly focused on data centers, since it integrates sensor and server status data. We are developing a system that gives a broad view of a data center, integrating server data such as CPU and memory usage or network bandwidth with room health parameters such as temperature, humidity, and power consumption or the presence sensors that indicate if there were people inside the room at the time a certain event occurred. As this is a work in progress, in this paper, we present the state-of-the-art of this subject, as well as what we expect to obtain from this project. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Fully Automatic Method for the Visual Acuity Estimation Using OCT Angiographies
Proceedings 2020, 54(1), 57; https://doi.org/10.3390/proceedings2020054057 - 04 Sep 2020
Viewed by 517
Abstract
In this work we propose the automatic estimation of the visual acuity of patients with retinal vein occlusion using Optical Coherence Tomography by Angiography (OCTA) images. To do this, we first extract the most relevant biomarkers in this imaging modality—area of the foveal [...] Read more.
In this work we propose the automatic estimation of the visual acuity of patients with retinal vein occlusion using Optical Coherence Tomography by Angiography (OCTA) images. To do this, we first extract the most relevant biomarkers in this imaging modality—area of the foveal avascular zone and vascular densities in different regions of the OCTA image. Then, we use a support vector machine to estimate the visual acuity. We obtained a mean absolute error of 0.1713 between the manual visual acuity measurement and the estimated, being considered satisfactory results. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Development of Recreational Content with Micro:Bit for Intervention with People with Cerebral Palsy
Proceedings 2020, 54(1), 58; https://doi.org/10.3390/proceedings2020054058 - 04 Sep 2020
Viewed by 643
Abstract
This paper presents a project carried out to use games in therapies for people with cerebral palsy. A Micro:bit board is used to have a friendly interaction between the user and the game. Through a simple interface, the therapist can manage the parameters [...] Read more.
This paper presents a project carried out to use games in therapies for people with cerebral palsy. A Micro:bit board is used to have a friendly interaction between the user and the game. Through a simple interface, the therapist can manage the parameters of the therapy and see the evolution of the user. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Predicting Gastric Cancer Molecular Subtypes from Gene Expression Data
Proceedings 2020, 54(1), 59; https://doi.org/10.3390/proceedings2020054059 - 07 Sep 2020
Viewed by 604
Abstract
Stomach cancer is a complex disease and one of the leading causes of cancer mortality in the world. With the view to improve patient diagnosis and prognosis, it has been stratified into four molecular subtypes. In this work, we compare the results of [...] Read more.
Stomach cancer is a complex disease and one of the leading causes of cancer mortality in the world. With the view to improve patient diagnosis and prognosis, it has been stratified into four molecular subtypes. In this work, we compare the results of multiple machine learning algorithms for the prediction of stomach cancer molecular subtypes from gene expression data. Moreover, we show the importance of decorrelating clinical and technical covariates. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Electronic Health Records Exploitation Using Artificial Intelligence Techniques
Proceedings 2020, 54(1), 60; https://doi.org/10.3390/proceedings2020054060 - 09 Sep 2020
Viewed by 683
Abstract
The exploitation of electronic health records (EHRs) has multiple utilities, from predictive tasks and clinical decision support to pattern recognition. Artificial Intelligence (AI) allows to extract knowledge from EHR data in a practical way. In this study, we aim to construct a Machine [...] Read more.
The exploitation of electronic health records (EHRs) has multiple utilities, from predictive tasks and clinical decision support to pattern recognition. Artificial Intelligence (AI) allows to extract knowledge from EHR data in a practical way. In this study, we aim to construct a Machine Learning model from EHR data to make predictions about patients. Specifically, we will focus our analysis on patients suffering from respiratory problems. Then, we will try to predict whether those patients will have a relapse in less than 6, 12 or 18 months. The main objective is to identify the characteristics that seem to increase the relapse risk. At the same time, we propose an exploratory analysis in search of hidden patterns among data. These patterns will help us to classify patients according to their specific conditions for some clinical variables. Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
Proceedings
Machine Learning to Compute Implied Volatility from European/American Options Considering Dividend Yield
Proceedings 2020, 54(1), 61; https://doi.org/10.3390/proceedings2020054061 - 15 Sep 2020
Viewed by 776
Abstract
Computing implied volatility from observed option prices is a frequent and challenging task in finance, even more in the presence of dividends. In this work, we employ a data-driven machine learning approach to determine the Black–Scholes implied volatility, including European-style and American-style options. [...] Read more.
Computing implied volatility from observed option prices is a frequent and challenging task in finance, even more in the presence of dividends. In this work, we employ a data-driven machine learning approach to determine the Black–Scholes implied volatility, including European-style and American-style options. The inverse function of the pricing model is approximated by an artificial neural network, which decouples the offline (training) and online (prediction) phases and eliminates the need for an iterative process to solve a minimization problem. Meanwhile, two challenging issues are tackled to improve accuracy and robustness, i.e., steep gradients of the volatility with respect to the option price and irregular early-exercise domains for American options. It is shown that deep neural networks can be used as an efficient numerical technique to compute implied volatility from European/American options. An extended version of this work can be found in . Full article
(This article belongs to the Proceedings of 3rd XoveTIC Conference)
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