Currently, studies have shown that one in three people infected with coronavirus disease-19 (COVID-19) is likely to have had long-term exposure to COVID-19, known as long-term COVID-19. Clinical studies indicate that many people infected with the severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) COVID-19 pandemic have long-term COVID-19 exposure. According to the study, it has been said that people with diabetes and obesity, and people who have received organ transplants, are more likely to suffer from this long-term effect of COVID-19. In this article, the effects of long-term COVID-19 exposure on neurological disability patients are analyzed with the help of a neuromachine learning model. The proposed model also shows that this long-term COVID problem does not depend on the factors such as race, age, gender, and socioeconomic status of those people. According to the proposed model, people suffering from long-term COVID problems continue to suffer from physical fatigue and shortness of breath and are regularly monitored and classified as per the proposed instructions. Even after they recover from the disease, various side effects are seen.

The core idea of asynchronous transfer mode (ATM) technology was revealed a long time ago. The main technology under development at the time was time-division multiplexing (TDM) technology, which consisted of synchronous switching based on the sequence number of bytes in the integrated frame. The main disadvantage of TDM technology, also known as synchronous transport module (STM) synchronous transmission technology, is the inability to reallocate the bandwidth of the integrated channel between subchannels. During those periods when no user data is sent on the subchannel, the aggregated channel still sends the bytes of this subchannel filled with zeros. Efforts to load sub channels’ idle periods necessitate the introduction of a header for each subchannel’s data. In intermediate statistical time-division multiplexing (STDM) technology, which allows idle periods to be filled by transmitting bursts of traffic from other sub channels, headers that actually have a subchannel number are introduced. In this paper, the strategic analysis and operation of technologies used in multiservice networks were discussed. Simultaneously, the structure of data sets is drawn into sets resembling computer networks. The fact that each packet has an address allows it to be transmitted asynchronously since its location relative to data on other subchannels is not its address. Asynchronous packets from one subchannel are inserted into the free time slots of another subchannel, but they are not mixed with the data of this subchannel because they have their own address.

onfidentialinformationisofgreatinteresttocompetingfirms.Thiscausesaggressionandattacks.Many people underestimate the importance of the threat, and as a result, it can lead to collapse and bankruptcy for the company. Even a single case of malpractice can result in millions in damages and the loss of customer trust. Threats are subject to data on organization structure, status, and operations. Sources of such threats are its competitors, corruptofficials,andcriminals.Theyareintroducedwithcertainvalue-protectedinformationandmodifiedinorder to cause financial damage. Even 20% of such a decision can result in information leakage. Sometimes the loss of companysecretscanbeduetotheinexperienceofemployeesoralackofsecuritysystems.Inthispaper,animproved intelligence approach to handling data leakage risks in the corporate information security process is proposed. Accounting automatically calculates weighted relative class systems through a complete, complex security of the most important processes and technical and organizational measures. Their combination is an antivirus system, a firewall, and protection from electromagnetic radiation. Systems protect information on electronic media sent through communication channels, access exemptions for various documents, create backup copies, and recover confidential information after damage.