Application of GPU Accelerated Deep Learning Neural Networks for COVID-19 Recognition from X-Ray Scans

In this paper we are presenting the results of creation and training of a stand-alone expert system aimed at detection and diagnosis of COVID infection, that is based on automatic readings of X-ray imaging X Ray, which determines whether the patient has COVID pneumonia. The system is realized with deep learning neural networks and is accelerated with GPU utilized, instead of CPU. © 2022 IEEE.

Improving the Accuracy of Rapid Antigen Tests for Covid-19 using Data Mining and Blood Test

PCR tests are known to give the most accurate results, but are not suitable for mass testing. This article suggests the use of data extraction to diagnose Covid-19. For this purpose, data from rapid antigen tests, external signs of infection and general blood count are processed. The result is that the reliability of antigen tests increases from 50% to over 72%. The future development of the system is to generate a hypothesis about the likelihood of complex application of Covid-19. PCR tests are known to give the most accurate results, but are not suitable for mass testing. © 2022 IEEE.

Comparative study of selected cryptocurrency

In the last few years, blockchain technologies have gained immense popularity both among researchers and in socio-economic life. Companies from various fields of industry implement projects based on blockchain technology. Pandemics like Covid-19 put almost all industries to the test. The work of the transport industry during the crisis is directly related to the work of the financial and banking sector. The problems that transport companies would experience from blocking the banking system during a subsequent pandemic would be solved in an innovative way using different cryptocurrencies. This article aims to make a comparative analysis of some cryptocurrencies, as well as to comment on the problems associated with them. The analysis can be used to develop blockchain-based applications in the transport industry.

Application of a memristive neural network for classification of covid-19 patients

The global pandemic of COVID-19 has affected the lives of millions around the globe. We learn new facts about this corona virus every day. A contribution to this knowledge is described in the paper and it is related to employment of memristor neural networks and algorithms that help us analyze patients’ data and determine what patients are at increased risk for developing severe medical conditions once infected with the COVID-19. An efficient separation of potential patients in ill and healthy sub-groups is conducted using software and hardware neural networks, machine learning and unsupervised clustering. In the recent years, many works are related to reducing of neural chips area for the hardware realization of neural networks. For this purpose, a partial replacement of CMOS transistors in neural networks by memristors is made. Some of the main memristor advantages are its lower power consumption, nano-scale sizes, sound memory effect and a good compatibility to CMOS technology. In this reason, the main purpose of this paper is application of a memristor-based neural network with tantalum oxide memristor synapses for COVID-19 analysis. Additional experiments with data clustering are conducted. Experiments show that in fact patients with specific underlying health conditions and indicators are more predisposed to develop severe COVID-19 illness. This research is helpful for engineers and scientists to easier identifying patients that would need medical help. © 2021, North Atlantic University Union NAUN. All rights reserved.

Analysis and Evaluation of Distance Schooling and Learning with Respect to ICT Usage During COVID-19 Period in Bulgaria

The article presents a national platform for sharing educational resources under a project of the Ministry of Education and Science in Bulgaria within the measures taken to support the educational process during the pandemic of the new coronavirus. As part of the team for development, implementation and business analysis of the above platform, the authors examine the country’s readiness to move from present to distance learning, analyze the context in which information technology is used in the educational process and the effectiveness and impact of the national electronic library for shared educational resources. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.