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SpringerBriefs in Applied Sciences and Technology ; : 35-39, 2023.
Article in English | Scopus | ID: covidwho-2326570


The coronavirus disease 2019 pandemic not only precipitated a digital revolution but also led to one of the largest scientific collaborative open-source initiatives. The EXaSCale smArt pLatform Against paThogEns for CoronaVirus (EXSCALATE4CoV) consortium, led by Dompé farmaceutici S.p.A., brought together 18 global organizations to counter international pandemics more rapidly and efficiently. The consortium also partnered with Nanome, an extended reality software company whose software facilitates the visualization, modification, and simulation of molecules via augmented reality, mixed reality, and virtual reality applications. To characterize the molecular structure of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and to identify promising drug targets, the EXSCALATE4CoV team utilized methods such as homology modeling, molecular dynamics simulations, high-throughput virtual screening, docking, and other computational procedures. Nanome provided analysis of those computational procedures and supplied virtual reality headsets to help scientists better understand and interact with the molecular dynamics and key chemical interactions of SARS-CoV-2. Nanome's collaborative ideation platform enables scientific breakthroughs across research institutions in the fight against the coronavirus pandemic and other diseases. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

NeuroQuantology ; 20(22):2590-2602, 2022.
Article in English | EMBASE | ID: covidwho-2323909


A current COVID-19 detection tool is CXR imaging, which has been developing since 2019 to provide early diagnosis;it can be performed in any health unit and is more affordable than Real Time Polymerase Chain Reaction (RT-PCR) tests. However, diagnosis with Chest X Ray (CXR) images had not achieved the predictive capacity required to replace the RT-PCR test;previous studies with a limited number of images have evaluated their models. This research seeks to contribute to the detection of COVID-19 from CXR images, with the evaluation of a convolutional neural network model from CXR images, through the use of open source code on a free dataset of approximately 30 thousand images. The algorithm and mathematical model used was DenseNet-201. The results of the experiment show a precision and accuracy of more than 95% and specificity, sensitivity, predictive ability and F1 measurement of more than 90%.Copyright © 2022, Anka Publishers. All rights reserved.

17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2323383


In this paper a numerical methodology for close proximity exposure (<2m) is applied to the analysis of aerosol airborne dispersion and SARS-CoV-2 potential infection risk during short journeys in passenger cars. It consists of a three-dimensional transient Eulerian-Lagrangian numerical model coupled with a recently proposed SARS-CoV-2 emission approach, using the open-source software OpenFOAM. The numerical tool, validated by Particle Image Velocimetry (PIV), is applied to the simulation of aerosol droplets emitted by a contagious subject in a car cabin during a 30-minute journey and to the integrated risk assessment for SARS-CoV-2 for the other passengers. The effects of different geometrical and thermo-fluid-dynamic influence parameters are investigated, showing that both the position of the infected subject and the ventilation system design affect the amount of virus inhaled and the highest-risk position inside the passenger compartment. Calculated infection risk, for susceptible passengers in the car, can reach values up to 59%. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

2023 IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2023 ; : 840-845, 2023.
Article in English | Scopus | ID: covidwho-2319208
22nd IEEE International Conference on Software Quality, Reliability and Security Companion, QRS-C 2022 ; : 708-717, 2022.
Article in English | Scopus | ID: covidwho-2299281
55th Annual Hawaii International Conference on System Sciences, HICSS 2022 ; 2022-January:316-325, 2022.
Article in English | Scopus | ID: covidwho-2296655
Lean & Six Sigma Review ; 22(1):8-13, 2022.
Article in English | ProQuest Central | ID: covidwho-2291969
26th International Computer Science and Engineering Conference, ICSEC 2022 ; : 49-54, 2022.
Article in English | Scopus | ID: covidwho-2268149
11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022 ; : 1451-1455, 2022.
Article in English | Scopus | ID: covidwho-2264321
15th International Conference on Application of Fuzzy Systems, Soft Computing and Artificial Intelligence Tools, ICAFS 2022 ; 610 LNNS:564-571, 2023.
Article in English | Scopus | ID: covidwho-2263897
10th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2021 and 11th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2022 ; 13822 LNCS:119-133, 2023.
Article in English | Scopus | ID: covidwho-2261537
8th International Conference on Contemporary Information Technology and Mathematics, ICCITM 2022 ; : 130-134, 2022.
Article in English | Scopus | ID: covidwho-2251407
5th International Conference on Communications, Signal Processing, and their Applications, ICCSPA 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2250822
Neurology Perspectives ; 3(1) (no pagination), 2023.
Article in English, Spanish | EMBASE | ID: covidwho-2250780
2022 RIVF International Conference on Computing and Communication Technologies, RIVF 2022 ; : 578-583, 2022.
Article in English | Scopus | ID: covidwho-2236571


Video-conferencing applications are becoming increasingly popular, especially with the remote working trend after COVID-19. The benefits of meeting online cannot be denied;however, this is still quite limited. In particular, it is essential to monitor and analyze participants' behavior. In this paper, we proposed SunFA - an open-source participants analysis tool for video-conferencing based on face analysis and virtual camera technology. The advantage of our system is that it is compatible with almost available video conferencing applications, such as Google Meet, Skype, Microsoft Teams, Zoom, Slack, etc. Furthermore, we packaged this software as a desktop application for Windows operating system to make it easy to install. The memory usage and execution time evaluation ensure the real-time and resource-saving of a video-conferencing application. We open-source our entire source code and solutions at © 2022 IEEE.

3rd International Conference on Computing, Analytics and Networks, ICAN 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2232100


With the emergence of coronavirus and the rapidly increasing number of cases, we observed that people were suffering from a lack of information about where to source critical requirements such as oxygen cylinders, beds, ambulance service, and ventilators. In this research paper and project, the authors have designed and developed an interactive information dashboard to access the availability of these resources and requirements at different locations across India from myriad sources. The information dashboard will show information for all the states across India. The dashboard visualizes the number of corona cases, hospital beds, blood bank, etc. The end-users and the COVID-19 support team can imagine all the requirements in the dashboard that is factual and credible within their vicinity from multiple information sources. The user need not search various information sites to search for different conditions. The project collates the data of other requirements from primary sources of information like Twitter and government websites and lists them on the dashboard. The authors used open-source programming and database technologies to display the data per user requirements. The dashboard was helpful to the end-users during COVID-19 times in terms of convenient accessibility and efficiency. © 2022 IEEE.

21st IFAC Conference on Technology, Culture and International Stability, TECIS 2022 ; 55:437-442, 2022.
Article in English | Scopus | ID: covidwho-2231070


Covid-19 pandemic has impacted every aspect of our society. One of the worst affected parts is the countries' health systems. Our goal is to provide a proof of concept for cost effective automated delivery system which can be used by hospitals for distributing medicine and food to patients in non-intensive wards, so medical personnel exposure to the virus can be minimized. Only free and open source software tools are used. Working proof of concept of the system is created consisted of: robot platform running ROS, SQL Server relational database, Web App. Limitations are identified. Testing is successful. We have showed that using free and open-source software and tools, it is possible to achieve the goal of creating the system. Copyright © 2022 The Authors.

Indian Journal of Agricultural Sciences ; 92(2):158-163, 2022.
Article in English | Web of Science | ID: covidwho-2207230