H. I. Mustafa et al (2020) describes In the application method (detection, prediction and selection, guessing) time series study Covid 19 to find the best Autoregressive Integrated Moving Average (ARIMA) to predict the number of people affected in Iraq. The swarm used collected between 1-March and 31-July. The results show that the corresponding prediction is for model ARIMA (2,1,5). Based on this model, they predict daily thirty-day numbers for those affected by COVID 19. The predicted value indicates the sample capacity, and the original series value is consistent.
P. Cihan (2020) describes Covid 19 integrated into the classification tools to diagnose infectious lung diseases such as the following, in conjunction with medical science up to AI (Artificial Intelligence). Four conditions were evaluated for Covid 19 pneumonia, non-Covid 19 pneumonia, pneumonia and normal lung. The AI system is divided into 2 stages. In the first stage, chest X-ray pneumonia and non-pneumonia are classified as one. Phase 2 should be obtained with stage 1 if fluoroscopy belongs to the lung type, and a Covid 19 positive and Covid 19 negative input are further classified.
S. Tabik et al. (2020) describes as Coronavirus disease (COVID 19) is one of the most contagious diseases of the 21st century, using RT-PCR detection, CT scan and / or chest X-ray (NHA) image detection. CT scanners and RT-PCR scans in many cases CXR images are an effective tool to assist clinicians in making most of the time / expense, therefore, most medical centers are available. Deep learning neural networks have great potential to develop a system for classifying COVID 19 and detect COVID 19 patients, especially at low levels. Unfortunately, the current databases are multifaceted and do not allow the establishment of such systems because they discriminate in more serious cases.
V. Z. Marmarelis et al (2020) described as Covid 19 Infectious Dynamics Analysis in order to guide socio-political decision making, appropriate preventive measures to assist in its reasonable planning in predicting critical outbreak disease, and to According to the established sir system framework the work should include multiple "vulnerable", "infectious" and "recovery / delete" scores per population, and define the dynamic relationship of the first-order differential equation.
X. Wang et al. (2020) described as Accurate and rapid diagnosis of COVID, 19 suspected cases plays an important role in timely isolation and medical treatment. Chest CD Automatic COVID 19 Diagnosis In-depth learning pattern development may be helpful in combating SARS-cov-2 outbreak. Deep learning within the weak structure is to use the COVID 19 classification and the module of the three-dimensional transformer to create the location of the decay. Lung region net segmentation for each patient uses a pre-exercise; then the 3D lung region is classified sent to the 3D deep neurological network to predict the probability of infection with COVID 19; COVID 19 translates into a combination of decay activation area and a classification network of unattended connected components. 499 CD Module Training and Testing 131 Transformer module is used.
X. Ouyang et al (2020) described as the 3D Convolutional Network (CNN) diagnostic decision-making online attention module, with the lungs in the main affected area. It is noteworthy that for the rapid exacerbation of COVID 19 after the onset of partial symptoms there is an asymmetry in the volume distribution in the affected area between COVID 19 and the cap. Therefore, the developed a dual model strategy to eliminate unbalanced learning. Our method is the data of the largest multi-core transformer COVID from 19 8 hospitals. During the training verification phase, the collected 1588 patients with 5 times more cross-examination than 2186 CT scans. In the trial phase, an used another independent large data set that tested 2796 CT scans of 2057 patients.
R. F. Sear et al (2020) described as Dangerous COVID 19 there is a huge amount of misconduct on the internet. The learning machine to measure the content of COVID 19, health guidance, especially vaccine ("anti-VAX") online antagonist. A found that the development of the anti-VAX community around COVID 19 a less focused litigation ("VAX pro") community than its counterpart. However, - in the anti-VAX community it is possible to obtain a broad cross-section of the COVID 19 vaccine, such as personal surveillance or mandatory rapid monitoring guidance from individuals. Therefore, the appearance in the anti-VAX community is better to attract more new support from the pro-VAX community.
Adnan Shereen et al (2020) described as Coronavirus disease 19 (COVID 19) (SARS-cov-2) originated in Wuhan, China and spread all over the world causing severe respiratory disease corona 2 highly transmitted and viral infection. Genetic research reveals that bats may therefore be a potential major reservoir of SARS-CoV-2, a phylogenetic allele and acute respiratory disease (such as SARS) bad virus. Intermediate sources of origin and transmission humans are unknown, but transmission to a rapidly transmitted person has been widely confirmed. Are there any clinically approved antiviral drugs or vaccines to be used against COVID 19? However, some widespread antiviral drugs are being evaluated in clinical trials as a result of COVID-19, clinical recovery.
Hu, S et al (2020) described as Coronavirus disease 2019 (COVID 19) excluded in Wuhan, and has been controlled on the basis of infection. This epidemic of public safety involves great pressure on the national economy. Currently, some countries and regions of the world are still experiencing epidemics, and there is an urgent need to determine the epidemic situation and travel risks in this region. Realize the surrounding situation below a relatively fine level, and then make a reasonable sharing decision to promote productivity and job restructuring. In this study, COVID 19 infection assessment indicators were constructed using multiple source data. Computational evaluation of 736 granular phases using a geographic diagnostic model and a solution branch model.
Zhang, Y et al (2020) described as Many countries have overcome the challenge of the medical resources required for the COVID 19 test, which requires low-cost development, rapid instrumentation to detect and effectively diagnose a large number of viruses. Although a chest x-ray scan is an effective tool candidate if the tests are largely personalized up to this, the images produced by the scan should be accurately examined as soon as possible. COVID 19 Bilateral pulmonary parenchymal ground glass and lung integration are sometimes opaque, with a circular shape and peripheral lung distribution. In this task, our goal is to quickly extract such small areas as chest X-ray images that may contain COVID-19 features being detected.
Ouyang, X. et al (2020) described as COVID 19 has caused a global epidemic and has become a very urgent threat around the world. Great power and resources have been invested in the development of immune, disease analysis and treatment strategies. Although nucleic acid testing has been used primarily as a gold standard to confirm this viral RNA-based disease, research has shown that such a technique has a high false-negative rating, especially in patients in the early stages, so CT imaging confirmation is an important diagnostic method for positive COVID 19. Although the development of Artificial Intelligence (AI) computer assist systems based on CD COVID 19 is progressing rapidly, most existing methods can only classify the most advanced segmentation methods in the state when high level human intervention is possible.
Cecilia, J. et al (2020) described as Mobile Crowd Sensor (MCS) is a technology in which smartphones perceive devices such as forecasting, the hidden benefits of sharing data about other people within the community. The use of shared information is derived from the online social networks (OSN) embedded in MCS mobile devices which include two different trends (1) mobile sense, and (2) sensor community, original information. In this article, the present chronological development of infectious COVID 19 in Spain, and I summarize MCS research work that addresses the outbreak of COVID 19 in Spanish society. In fact, the risk of COVID 19 infection is being given in today’s society; the economy is greatly affected by the control of government and social gaps through action.
ONODA, H. (2020) described as COVID 19 Smart Way to Waste Japan After Active City Management The author's research team explains the results. In particular, the author points out that virtual reality distance education can be an effective solution. The job chain management system helps to promote non-cash in addition to waste detection. Supports multi-purpose handset system self-driving cars and links to smart junk so it can facilitate automatic junk collection.