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The following results are related to COVID-19. Are you interested to view more results? Visit OpenAIRE - Explore.
34 Research products, page 1 of 4

  • COVID-19
  • Publications
  • 2012-2021
  • English
  • WHO Global literature on coronavirus disease
  • Repositorio Digital Universidad Don Bosco
  • COVID-19

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  • Open Access English
    Authors: 
    Viktoriia Shubina; Aleksandr Ometov; Elena Simona Lohan;
    Publisher: IEEE
    Country: Finland
    Project: EC | A-WEAR (813278)

    The wearables' market is rapidly evolving, with applications ranging from healthcare and activity monitoring to emerging domains such as drones and haptic helmets. Wearable-based contact tracing is gaining increased attention in the COVID-19 era for more efficient disease prevention. Therefore, it is of timely relevance to identify the leading existing wireless contact-tracing solutions and their suitability for wearables. Existing trade-offs of contact-tracing applications require a thorough analysis of technical capabilities, such as accuracy, energy consumption, availability, sources of errors when dealing with wireless channels, privacy challenges, and deterrents towards a large-scale adoption on the wearables market. Based on extensive literature research, we conclude that decentralized architectures generally offer a better place in a trade-off in terms of accuracy and user eagerness to adopt them, taking into account privacy considerations, compared to centralized approaches. Our paper provides a brief technical overview of the existing solutions deployed for contact tracing, defines main principles that affect the overall efficacy of digital contact tracing, and presents a discussion on the potential effect of wearables in tackling the spread of a highly contagious virus. acceptedVersion Peer reviewed

  • Publication . Conference object . 2020
    Open Access English
    Authors: 
    Paolo Di Giamberardino; Daniela Iacoviello;
    Publisher: Institute of Electrical and Electronics Engineers Inc.
    Country: Italy

    COVID-19 has caused more than 880.000 victims all over the world (September 2020); despite a large effort of the scientific community and of the governments, it is still a great problem, inducing most of the Nations to adopt restriction to mo-bility, social relations and economic activities. Since the beginning of the pandemic, COVID-19 appeared a rather mysterious virus, for which neither a vaccination nor specific medications exist. In this paper, COVID-19 is characterized by using the available data of total number of infected, healed and dead people to identify the contagion, the removed and the death rates. These values depend on various aspects related to the population characteristics, the general health conditions, the social and economical situations, as well as to other features not yet identified by the scientific community. The COVID-19 situation in Italy is herein explored, showing the great heterogeneity of the virus spread in different zones.

  • Open Access English
    Authors: 
    Giacomo Mambelli; Catia Prandi; Silvia Mirri;
    Publisher: Institute of Electrical and Electronics Engineers Inc.
    Country: Italy

    Sentiment analysis, social networks analysis, and social media sensing are becoming important tools to extract meaningful information from text, adopted in several contexts, ranging from social interactions, touristic activities, shopping and e-commerce, to name a few. In particular, the current CoVid-19 quarantine the world is witnessing has shown the potential of such tools as a way to monitor and understand people’s mood and feelings, in a time where people are resorting, more than ever, to social networks to engage and communicate with others. Indeed, when performing social network content analysis, privacy is a major concern. On the one hand, privacy issues and international laws and acts drive such analysis (e.g., GDPR), with the aim of protecting persons’ privacy and security. On the other hand, these can limit somehow such activities. Hence, a precise and accurate identification of the strategies to adopt should be done to balance privacy issues and sentiment analysis activities. Taking into account the requirements of a Urban Innovation Action project, which is based on the active involvement of citizens, this work aims to describe limitations and potentialities of social networks monitoring and analysis to understand users’ mood about the project actions adopted in the city of Ravenna (in Italy) to improve specific districts.

  • Publication . Conference object . Article . 2020
    Open Access English
    Authors: 
    Elizabeth Douglas; Kristina A Fraser;
    Publisher: BMJ Publishing Group

    Background UNTHSC opened Fort Worth’s first drive-through coronavirus testing site which functioned as both a community service and an opportunity for health professional students to learn rapid cycle improvement. Nasopharyngeal swabs were administered through vehicle windows in what was referred to as ‘the hot zone.’ Throughout 12 weeks many changes were made to the hot zone, including installing a tent, adding a second lane, improving hot zone staff training, and staggering opening times. Objectives To ensure safe, efficient, and effective SARSCoV-2 testing for patients and staff. Methods Total tests and times per test were recorded. Time in PPE was calculated from the time PPE was donned to average time doffed. Positive test count was used as a metric for pathogen exposure. Total cases among staff were also recorded along with near misses, incidents, and good catches as discussed in daily team debrief. Training was standardized and videos were created for hot zone and safety officer staff. Results The site was open from March to June. With the tent, the accidental hot zone entry rate dropped from average of almost once per day to only once in 11 weeks. There were only 3 heat related incidents intercepted and 0 cases of COVID-19 among the 400 students and faculty. 8 safety incidents occurred. An average of 4 good catches or incidents prevented were counted per week. With staggering, time in full PPE was reduced from 165 minutes to 120 minutes. The record for most tests administered per shift increased from 55 for one lane to 112 for two lanes (figure 1). Conclusions Lessons learned here about heat safety, pathogen safety, and hot zone training can be applied to all drive thru testing sites. With this ongoing pandemic, it is wise to look for ways to improve test sites as well as potential vaccination sites.

  • Open Access English
    Authors: 
    Fawad Nawaz Khan; Rizwan Ahmad; Waqas Ahmed; Muhammad Mahtab Alam; Micheal Drieber;
    Publisher: IEEE
    Project: EC | COEL (668995)

    Link/channel scheduling is a process by which different channels within the allowed set of frequencies or different timeslots from a single channel are assigned to achieve minimum interference to the neighbouring nodes and higher efficiency. Existing channel scheduling approaches are often evaluated under the assumption of random mobility model. These approaches tend to average out interfering and non-interfering situations and the end results are not purely applicable to a consistent interference situation, such as the COVID-19 isolation centers. Therefore, in this paper, for a given interference level, we analyze the performance of the Interference and Priority aware Coexistence (IPC) algorithm. To this end, a controlled interference generation model is designed that can ensure consistent interference among a given number of Wireless Body Area Networks (WBANs). The performance is assessed in terms of delay, delivery, reuse, energy consumption, and throughput. Under controlled interference, the results show that the IPC algorithm guarantees better results as compared to existing link scheduling techniques.

  • Publication . Contribution for newspaper or weekly magazine . 2020
    Open Access English
    Authors: 
    Soujanya Mantravadi; Jag Srai; Thomas Ditlev Brunoe; Charles Møller;
    Publisher: IEEE
    Country: Denmark

    This paper explores the role of manufacturing execution systems (MES) with ISA 95 functionalities for the reconfigurability in a manufacturing enterprise. The work is aimed at supporting digitalization based on Industry 4.0 and the Industrial Internet of Things (IIoT) concepts. For this, we use the quality function deployment method to link ISA 95 MES functionalities and reconfigurability needs, based on a case example of a cyber-physical factory (AAU Smart Lab). Accordingly, we present a framework to assess reconfigurability for smart factory development. The paper identifies reconfigurability approaches using IIoT connected MES/MOM for tackling severe market disruptions (e.g. the one caused by the ongoing COVID-19 pandemic).

  • Open Access English
    Authors: 
    Jizhou Huang; Haifeng Wang; Miao Fan; An Zhuo; Yibo Sun; Ying Li;

    The constrained outbreak of COVID-19 in Mainland China has recently been regarded as a successful example of fighting this highly contagious virus. Both the short period (in about three months) of transmission and the sub-exponential increase of confirmed cases in Mainland China have proved that the Chinese authorities took effective epidemic prevention measures, such as case isolation, travel restrictions, closing recreational venues, and banning public gatherings. These measures can, of course, effectively control the spread of the COVID-19 pandemic. Meanwhile, they may dramatically change the human mobility patterns, such as the daily transportation-related behaviors of the public. To better understand the impact of COVID-19 on transportation-related behaviors and to provide more targeted anti-epidemic measures, we use the huge amount of human mobility data collected from Baidu Maps, a widely-used Web mapping service in China, to look into the detail reaction of the people there during the pandemic. To be specific, we conduct data-driven analysis on transportation-related behaviors during the pandemic from the perspectives of 1) means of transportation, 2) type of visited venues, 3) check-in time of venues, 4) preference on "origin-destination" distance, and 5) "origin-transportation-destination" patterns. For each topic, we also give our specific insights and policy-making suggestions. Given that the COVID-19 pandemic is still spreading in more than 200 countries and territories worldwide, infecting millions of people, the insights and suggestions provided here may help fight COVID-19. KDD 2020

  • Open Access English
    Authors: 
    Miguel Ribeiro; Valentina Nisi; Catia Prandi; Nuno Jardim Nunes;
    Publisher: Institute of Electrical and Electronics Engineers Inc.
    Country: Italy

    In this paper, we present a real-world study where a community-based tracking infrastructure has been put to good use for understanding human mobility during the COVID-19 outbreak, in order to contrast its diffusion. In particular, the infrastructure, deployed in 81 points of interests (POIs) across the Madeira Islands (Portugal), can collect a massive amount of spatio-temporal data, that can be enriched with potentially independent data sources of additional values (such as the official number of people affected by the coronavirus disease), and crowdsourced data collected by citizens. These enriched hyper-local data can be manipulated to provide i) stakeholders with a visual tool to contrast COVID-19 diffusion through human mobility monitoring, and ii) citizens with an interactive tool to visualize, in real-time, how crowded is a POI and plan their daily activities, and contribute to the data acquisition. Here we present the deployed community-based infrastructure and the data visualization interactive web application, designed to extract meaningful information from human mobility data during the COVID-19 outbreak.

  • Publication . Conference object . Preprint . Article . 2020
    Open Access English
    Authors: 
    Giuseppe Carlo Calafiore; Carlo Novara; Corrado Possieri;
    Country: Italy

    The purpose of this work is to give a contribution to the understanding of the COVID-19 contagion in Italy. To this end, we developed a modified Susceptible-Infected-Recovered (SIR) model for the contagion, and we used official data of the pandemic up to March 30th, 2020 for identifying the parameters of this model. The non standard part of our approach resides in the fact that we considered as model parameters also the initial number of susceptible individuals, as well as the proportionality factor relating the detected number of positives with the actual (and unknown) number of infected individuals. Identifying the contagion, recovery and death rates as well as the mentioned parameters amounts to a non-convex identification problem that we solved by means of a two-dimensional grid search in the outer loop, with a standard weighted least-squares optimization problem as the inner step.

  • Open Access English
    Authors: 
    Manoranjan Mohanty; Waheeb Yaqub;
    Publisher: IEEE
    Country: Australia

    © 2020 IEEE. The lockdowns and travel restrictions in the current coronavirus pandemic situation has replaced face-to-face teaching and meeting with the online alternatives. Recently, the video conferencing tool Zoom has become extremely popular for its simple-to-use features and low network bandwidth requirement. However, Zoom has serious security and privacy issues. Due to weak authentication mechanisms, unauthorised persons are invading Zoom sessions and creating disturbances (known as Zoom bombing). In this paper, we propose a preliminary work towards a seamless authentication mechanism for Zoom-based teaching and meeting. Our method is based on PRNU (Photo Response Non-Uniformity)-based camera authentication, which can authenticate the camera of a device used in a Zoom meeting without requiring any assistance from the participants (e.g., needing the participant to provide biometric). Results from a small-scale experiment validate the proposed method.

Advanced search in Research products
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
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Include:
The following results are related to COVID-19. Are you interested to view more results? Visit OpenAIRE - Explore.
34 Research products, page 1 of 4
  • Open Access English
    Authors: 
    Viktoriia Shubina; Aleksandr Ometov; Elena Simona Lohan;
    Publisher: IEEE
    Country: Finland
    Project: EC | A-WEAR (813278)

    The wearables' market is rapidly evolving, with applications ranging from healthcare and activity monitoring to emerging domains such as drones and haptic helmets. Wearable-based contact tracing is gaining increased attention in the COVID-19 era for more efficient disease prevention. Therefore, it is of timely relevance to identify the leading existing wireless contact-tracing solutions and their suitability for wearables. Existing trade-offs of contact-tracing applications require a thorough analysis of technical capabilities, such as accuracy, energy consumption, availability, sources of errors when dealing with wireless channels, privacy challenges, and deterrents towards a large-scale adoption on the wearables market. Based on extensive literature research, we conclude that decentralized architectures generally offer a better place in a trade-off in terms of accuracy and user eagerness to adopt them, taking into account privacy considerations, compared to centralized approaches. Our paper provides a brief technical overview of the existing solutions deployed for contact tracing, defines main principles that affect the overall efficacy of digital contact tracing, and presents a discussion on the potential effect of wearables in tackling the spread of a highly contagious virus. acceptedVersion Peer reviewed

  • Publication . Conference object . 2020
    Open Access English
    Authors: 
    Paolo Di Giamberardino; Daniela Iacoviello;
    Publisher: Institute of Electrical and Electronics Engineers Inc.
    Country: Italy

    COVID-19 has caused more than 880.000 victims all over the world (September 2020); despite a large effort of the scientific community and of the governments, it is still a great problem, inducing most of the Nations to adopt restriction to mo-bility, social relations and economic activities. Since the beginning of the pandemic, COVID-19 appeared a rather mysterious virus, for which neither a vaccination nor specific medications exist. In this paper, COVID-19 is characterized by using the available data of total number of infected, healed and dead people to identify the contagion, the removed and the death rates. These values depend on various aspects related to the population characteristics, the general health conditions, the social and economical situations, as well as to other features not yet identified by the scientific community. The COVID-19 situation in Italy is herein explored, showing the great heterogeneity of the virus spread in different zones.

  • Open Access English
    Authors: 
    Giacomo Mambelli; Catia Prandi; Silvia Mirri;
    Publisher: Institute of Electrical and Electronics Engineers Inc.
    Country: Italy

    Sentiment analysis, social networks analysis, and social media sensing are becoming important tools to extract meaningful information from text, adopted in several contexts, ranging from social interactions, touristic activities, shopping and e-commerce, to name a few. In particular, the current CoVid-19 quarantine the world is witnessing has shown the potential of such tools as a way to monitor and understand people’s mood and feelings, in a time where people are resorting, more than ever, to social networks to engage and communicate with others. Indeed, when performing social network content analysis, privacy is a major concern. On the one hand, privacy issues and international laws and acts drive such analysis (e.g., GDPR), with the aim of protecting persons’ privacy and security. On the other hand, these can limit somehow such activities. Hence, a precise and accurate identification of the strategies to adopt should be done to balance privacy issues and sentiment analysis activities. Taking into account the requirements of a Urban Innovation Action project, which is based on the active involvement of citizens, this work aims to describe limitations and potentialities of social networks monitoring and analysis to understand users’ mood about the project actions adopted in the city of Ravenna (in Italy) to improve specific districts.

  • Publication . Conference object . Article . 2020
    Open Access English
    Authors: 
    Elizabeth Douglas; Kristina A Fraser;
    Publisher: BMJ Publishing Group

    Background UNTHSC opened Fort Worth’s first drive-through coronavirus testing site which functioned as both a community service and an opportunity for health professional students to learn rapid cycle improvement. Nasopharyngeal swabs were administered through vehicle windows in what was referred to as ‘the hot zone.’ Throughout 12 weeks many changes were made to the hot zone, including installing a tent, adding a second lane, improving hot zone staff training, and staggering opening times. Objectives To ensure safe, efficient, and effective SARSCoV-2 testing for patients and staff. Methods Total tests and times per test were recorded. Time in PPE was calculated from the time PPE was donned to average time doffed. Positive test count was used as a metric for pathogen exposure. Total cases among staff were also recorded along with near misses, incidents, and good catches as discussed in daily team debrief. Training was standardized and videos were created for hot zone and safety officer staff. Results The site was open from March to June. With the tent, the accidental hot zone entry rate dropped from average of almost once per day to only once in 11 weeks. There were only 3 heat related incidents intercepted and 0 cases of COVID-19 among the 400 students and faculty. 8 safety incidents occurred. An average of 4 good catches or incidents prevented were counted per week. With staggering, time in full PPE was reduced from 165 minutes to 120 minutes. The record for most tests administered per shift increased from 55 for one lane to 112 for two lanes (figure 1). Conclusions Lessons learned here about heat safety, pathogen safety, and hot zone training can be applied to all drive thru testing sites. With this ongoing pandemic, it is wise to look for ways to improve test sites as well as potential vaccination sites.

  • Open Access English
    Authors: 
    Fawad Nawaz Khan; Rizwan Ahmad; Waqas Ahmed; Muhammad Mahtab Alam; Micheal Drieber;
    Publisher: IEEE
    Project: EC | COEL (668995)

    Link/channel scheduling is a process by which different channels within the allowed set of frequencies or different timeslots from a single channel are assigned to achieve minimum interference to the neighbouring nodes and higher efficiency. Existing channel scheduling approaches are often evaluated under the assumption of random mobility model. These approaches tend to average out interfering and non-interfering situations and the end results are not purely applicable to a consistent interference situation, such as the COVID-19 isolation centers. Therefore, in this paper, for a given interference level, we analyze the performance of the Interference and Priority aware Coexistence (IPC) algorithm. To this end, a controlled interference generation model is designed that can ensure consistent interference among a given number of Wireless Body Area Networks (WBANs). The performance is assessed in terms of delay, delivery, reuse, energy consumption, and throughput. Under controlled interference, the results show that the IPC algorithm guarantees better results as compared to existing link scheduling techniques.

  • Publication . Contribution for newspaper or weekly magazine . 2020
    Open Access English
    Authors: 
    Soujanya Mantravadi; Jag Srai; Thomas Ditlev Brunoe; Charles Møller;
    Publisher: IEEE
    Country: Denmark

    This paper explores the role of manufacturing execution systems (MES) with ISA 95 functionalities for the reconfigurability in a manufacturing enterprise. The work is aimed at supporting digitalization based on Industry 4.0 and the Industrial Internet of Things (IIoT) concepts. For this, we use the quality function deployment method to link ISA 95 MES functionalities and reconfigurability needs, based on a case example of a cyber-physical factory (AAU Smart Lab). Accordingly, we present a framework to assess reconfigurability for smart factory development. The paper identifies reconfigurability approaches using IIoT connected MES/MOM for tackling severe market disruptions (e.g. the one caused by the ongoing COVID-19 pandemic).

  • Open Access English
    Authors: 
    Jizhou Huang; Haifeng Wang; Miao Fan; An Zhuo; Yibo Sun; Ying Li;

    The constrained outbreak of COVID-19 in Mainland China has recently been regarded as a successful example of fighting this highly contagious virus. Both the short period (in about three months) of transmission and the sub-exponential increase of confirmed cases in Mainland China have proved that the Chinese authorities took effective epidemic prevention measures, such as case isolation, travel restrictions, closing recreational venues, and banning public gatherings. These measures can, of course, effectively control the spread of the COVID-19 pandemic. Meanwhile, they may dramatically change the human mobility patterns, such as the daily transportation-related behaviors of the public. To better understand the impact of COVID-19 on transportation-related behaviors and to provide more targeted anti-epidemic measures, we use the huge amount of human mobility data collected from Baidu Maps, a widely-used Web mapping service in China, to look into the detail reaction of the people there during the pandemic. To be specific, we conduct data-driven analysis on transportation-related behaviors during the pandemic from the perspectives of 1) means of transportation, 2) type of visited venues, 3) check-in time of venues, 4) preference on "origin-destination" distance, and 5) "origin-transportation-destination" patterns. For each topic, we also give our specific insights and policy-making suggestions. Given that the COVID-19 pandemic is still spreading in more than 200 countries and territories worldwide, infecting millions of people, the insights and suggestions provided here may help fight COVID-19. KDD 2020

  • Open Access English
    Authors: 
    Miguel Ribeiro; Valentina Nisi; Catia Prandi; Nuno Jardim Nunes;
    Publisher: Institute of Electrical and Electronics Engineers Inc.
    Country: Italy

    In this paper, we present a real-world study where a community-based tracking infrastructure has been put to good use for understanding human mobility during the COVID-19 outbreak, in order to contrast its diffusion. In particular, the infrastructure, deployed in 81 points of interests (POIs) across the Madeira Islands (Portugal), can collect a massive amount of spatio-temporal data, that can be enriched with potentially independent data sources of additional values (such as the official number of people affected by the coronavirus disease), and crowdsourced data collected by citizens. These enriched hyper-local data can be manipulated to provide i) stakeholders with a visual tool to contrast COVID-19 diffusion through human mobility monitoring, and ii) citizens with an interactive tool to visualize, in real-time, how crowded is a POI and plan their daily activities, and contribute to the data acquisition. Here we present the deployed community-based infrastructure and the data visualization interactive web application, designed to extract meaningful information from human mobility data during the COVID-19 outbreak.

  • Publication . Conference object . Preprint . Article . 2020
    Open Access English
    Authors: 
    Giuseppe Carlo Calafiore; Carlo Novara; Corrado Possieri;
    Country: Italy

    The purpose of this work is to give a contribution to the understanding of the COVID-19 contagion in Italy. To this end, we developed a modified Susceptible-Infected-Recovered (SIR) model for the contagion, and we used official data of the pandemic up to March 30th, 2020 for identifying the parameters of this model. The non standard part of our approach resides in the fact that we considered as model parameters also the initial number of susceptible individuals, as well as the proportionality factor relating the detected number of positives with the actual (and unknown) number of infected individuals. Identifying the contagion, recovery and death rates as well as the mentioned parameters amounts to a non-convex identification problem that we solved by means of a two-dimensional grid search in the outer loop, with a standard weighted least-squares optimization problem as the inner step.

  • Open Access English
    Authors: 
    Manoranjan Mohanty; Waheeb Yaqub;
    Publisher: IEEE
    Country: Australia

    © 2020 IEEE. The lockdowns and travel restrictions in the current coronavirus pandemic situation has replaced face-to-face teaching and meeting with the online alternatives. Recently, the video conferencing tool Zoom has become extremely popular for its simple-to-use features and low network bandwidth requirement. However, Zoom has serious security and privacy issues. Due to weak authentication mechanisms, unauthorised persons are invading Zoom sessions and creating disturbances (known as Zoom bombing). In this paper, we propose a preliminary work towards a seamless authentication mechanism for Zoom-based teaching and meeting. Our method is based on PRNU (Photo Response Non-Uniformity)-based camera authentication, which can authenticate the camera of a device used in a Zoom meeting without requiring any assistance from the participants (e.g., needing the participant to provide biometric). Results from a small-scale experiment validate the proposed method.