COVID-19 prediction based on hybrid Inception V3 with VGG16 using chest X-ray images.

The Corona Virus was first started in the Wuhan city, China in December of 2019. It belongs to the Coronaviridae family, which can infect both animals and humans. The diagnosis of coronavirus disease-2019 (COVID-19) is typically detected by Serology, Genetic Real-Time reverse transcription-Polymerase Chain Reaction (RT-PCR), and Antigen testing. These testing methods have limitations like limited sensitivity, high cost, and long turn-around time. It is necessary to develop an automatic detection system for COVID-19 prediction. Chest X-ray is a lower-cost process in comparison to chest Computed tomography (CT). Deep learning is the best fruitful technique of machine learning, which provides useful investigation for learning and screening a large amount of chest X-ray images with COVID-19 and normal. There are many deep learning methods for prediction, but these methods have a few limitations like overfitting, misclassification, and false predictions for poor-quality chest X-rays. In order to overcome these limitations, the novel hybrid model called "Inception V3 with VGG16 (Visual Geometry Group)" is proposed for the prediction of COVID-19 using chest X-rays. It is a combination of two deep learning models, Inception V3 and VGG16 (IV3-VGG). To build the hybrid model, collected 243 images from the COVID-19 Radiography Database. Out of 243 X-rays, 121 are COVID-19 positive and 122 are normal images. The hybrid model is divided into two modules namely pre-processing and the IV3-VGG. In the dataset, some of the images with different sizes and different color intensities are identified and pre-processed. The second module i.e., IV3-VGG consists of four blocks. The first block is considered for VGG-16 and blocks 2 and 3 are considered for Inception V3 networks and final block 4 consists of four layers namely Avg pooling, dropout, fully connected, and Softmax layers. The experimental results show that the IV3-VGG model achieves the highest accuracy of 98% compared to the existing five prominent deep learning models such as Inception V3, VGG16, ResNet50, DenseNet121, and MobileNet.

Assessment Of Covid-19 Vaccination Literacy And Post Vaccination Effects Among Vaccinated Population: A Cross-Sectional Online Survey Study

BACKGROUND: A safe and effective vaccine against COVID-19 has become a public health priority. However only a few studies have been conducted to investigate the post vaccination symptoms and awareness among the public about the vaccination. This study aimed to assess the COVID-19 vaccination literacy and post vaccination effects among the vaccinated population in India. METHODOLOGY: A descriptive cross-sectional study was conducted with a convenience sample of the adult population in India. Data was collected through an online anonymous questionnaire. We used Google forms an online survey platform, to publish the questionnaire and manually generated the answer URL link to the eligible candidates. RESULTS: A total of 533 responses were collected. Among the participants, 463 (86.90%) were aged between 18 and 40 years old. Of which 289 (54.2%) were male and 244 (45.8%) were female participants. Among the respondents 374 (70.2%) completed both the doses of vaccine. 498 (93.4%) participants took the vaccination willingly and 35 (6.6%) participants were forced to get vaccinated. Body ache 327 (61.4%), Fever 307 (57.6%), headache 211 (39.6%) and alopecia 70 (14%) were the most commonly reported post vaccination symptoms. CONCLUSION: Overall, our study demonstrated that there was a high willingness to accept COVID-19 vaccine in India and the rate of infection with COVID-19 has been reduced after vaccination which proves that the vaccine is efficient. The rate of people getting hospitalized due COVID-19 has been drastically reduced. Cold, cough, mild hypersensitivity reactions were also been reported as post vaccination symptoms and no serious adverse effects were reported so far due to vaccination which proves that the vaccine is safe. [ FROM AUTHOR] Copyright of Journal of Pharmaceutical Negative Results is the property of ResearchTrentz and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Accelerating a safe and effective control measures for Covid-19 pandemic: Water, sanitation and wash

Current situation in our country is been suffering from a dangerous disease called corona virus which is seen both creatures and human beings. SARS (Severe Acute Respiratory Syndrome) -COV is an example for corona virus.Retrosepective observation by Chinese people have seen many number of cases with start of manifestation in the month of December 2019[1].The first case was seen in china with different types of symptoms and it is known that it was a transmittable disease.Many people who are suffering with this will have an illness which is related to respiration part and it will be cured after taking the period of quarantine for 14 days, with any different kinds of treatments at home or an advice of doctors. Some people who are been affected others health issues will develop serious illness. Around 90% of the people are recovered without undergoing any special treatments because they themselves taking quarantine at home by following home remedies. But some people are being suffering with trouble breathing [5].In the month of March 11 2020 (WHO) recognized and declared it as an pandemic which has spread in many parts of the country within less span of time. This virus was first seen in a city called Wuhan, state of China. In the month of December 2019 the reports of the first COVID-19 cases have started. Yet, it is undecided exactly the spread of this virus and it is spreading very faster in humans. This paper tells about control and safety measures regarding water, sanitation, wash in covid-19 pandemic [1] and following the prevention methods critically is very essential to avoid the spread of this virus.Maintaining cleanliness, following all the rules, and advising your loved ones to do likewise for averting the transmission of SARS-CoV-2. © 2022 Author(s).

Artificial Intelligence based Forecasting Techniques for the Covid-19 pandemic

The burial of bodies became a trend in the cause of ongoing pending (Novel Coronavirus), more than50 a million people all over the globe are adversely affected, hence the analysis and forecasting techniques are necessary to regain the human livelihood. The enlargement of technologies such as Artificial Intelligence, Machine Learning, Deep Learning, are en route into all the living aspects. Hence by using AI, ML, DL, Advanced technologies and existing models ARIMA, PROPHET, SVM, RNN, Faster Mask R-CNN, RESNET-50, and other techniques such as logarithmic scaling and exponential smoothing so on, the spread of VIRUS, the effect of countries economic growth, confirmed cases, fatality rate, recoveries are predicted to overcome the life threat due to SARS. Such that different predictive techniques are used to forecast. The advancement in the past algorithms to acquire accurate results are been introduced and described. © 2022 IEEE.

CRaaS: Cyber Range as a Service

The Internet and networking have evolved substantially into new forms and types. These technologies are used by everyone in the 21st century. After the COVID pandemic, everything has become more virtual, and most transactions, including studies, were accomplished online. With the growth in technology and services, the risk of them being exploited increases. Cybersecurity is a collection of technologies, procedures, and practices aimed at preventing attacks, damage, and illegal access to networks, devices, programs, and data. Overcoming the cybersecurity challenges is even more complicated due to the lack of training and unavailable cybersecurity environments. Cybersecurity experiments must be run in a realistic and controllable environment. In this work, we have set up a virtual environment to provide the required resources for the user to learn cybersecurity skills. We have demonstrated eight cyber attacks. Each attack is provided with a demo video and an automated version of the attack. The user is provided with steps to practice how the attack works and instructions to mitigate these attacks. These resources are made available on-demand to the user through a web portal. The performance analysis has been done for every attack. The launch time of the automated attacks is also recorded and analyzed. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Biology, prevention, and treatment of SARS-CoV-2 (COVID-19)

The spread of the SARS-CoV-2 novel coronavirus, the cause of the COVID-19 pandemic, has recently emerged as a global concern. It has spread rapidly across the globe, which originally began in the town of Wuhan in the People’s Republic of China and is believed to come from the community of Rhinolophus bats. In this chapter we have discussed the basic biological features of the virus including how it replicates and causes the disease. In addition, we reviewed how does the virus spread and what interventions limit the spread. We also discussed the most promising drugs from clinical trials and preclinical developments to date. © 2021 Elsevier Inc. All rights reserved.

Drunkenness Face Detection using Graph Neural Networks

The fatalities associated with driving while intoxicated (DWI) are on the rise, leading to a staggering twelve thousand people dying from it and nine lakh people getting arrested every year. DWIs are usually confirmed with the use of breathalyzers, which require the subject to blow into the machine. In light of the current pandemic caused by COVID-19, a susceptible individual may deny blowing into the machine. Thus, the need for a contactless method to detect if someone is drunk arises, so that suspects are prevented from taking advantage of the situation. This also assists law enforcement in the detection of DWI cases. The proposed study is the method to detect intoxication in a given suspect through Graph Neural Networks using facial landmarks. We also present a labeled dataset as a complementary dataset for intoxication detection. This dataset is the first graph-based data available for the detection of alcohol intoxication. Extensive experiments were carried out to validate this approach. © 2021 IEEE.

A Deep Analysis of Higher Education Cognitive and Psychological Learning Impact During Covid 19 Pandemic

Current scenario around the globe we can find that physical or face to face learning got a very big full stop for a long period of time. Virtual learning took its place, somewhat leaving behind both its positive and negative impact on the education sector. E-learning is playing a chief part in maintaining the decorum of education sector. The research and surveys found that young learners got many benefits through this type of education but also it is undeniable that it has negative aspects too, which needs to be solved. Mainly private higher education suffered less as compared to institutions in rural areas. This research proposes how to bring out the quality of output through e-learning for all the learners equally. It has become a challenge for private and government institutions to make this smart or virtual learning as the best integral part of educational system. © 2021 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).

Mathematical models for predicting COVID-19 pandemic: A review

The catastrophic outbreak of the Novel Corona virus (Covid-19) has brought to light, the significance of reliable predictive mathematical models. The results from such models greatly affect the use of non-pharmaceutical intervention measures, management of medical resources and understanding risk factors. This paper compares popular mathematical models based on their predictive capabilities, practical validity, presumptions and drawbacks. The paper focuses on popular techniques in use for the predictive modeling of the Covid-19 epidemic. The paper covers the Gaussian Model, SIRD, SEIRD and the latest θ-SEIHRD techniques used for predictive modeling of epidemics. © 2021 Institute of Physics Publishing. All rights reserved.

Challenges in online teaching amidst covid crisis: Impact on engineering educators of different levels

COVID-19 thrashed the field of education with a greater challenge by sudden forced closure of educational institutions and to seek for alternative approaches in present mandatory forced physical distancing. The task of efficiently tune the learners to equip with global competencies and to nurture the skill for developing services to meet the utmost requirements of the society. As the present condition is uncertain and keeping this aspect in view, as a best compensation to the existing forced loss to learners, the educational institutions in India adopted virtual mode for regular teaching and learning processes. Virtual approach is not a new mode but it was confined to special learning aspects rather than traditional mode of teaching as of now. Under these circumstances, being an immediate alternative to the existing huge loss, several challenges need to be addressed such as the immediate adoption of this online pedagogy by engineering educators of different levels. The present paper describes the results of survey conducted on teachers of different levels and different specialisations conducted in July-August 2020. In the first phase of study, the survey is conducted among senior career educators regarding the faculty and learner confidence in technology enabled learning and in the second phase of study, the extent of interaction by the educators with the learners and parents and Technological Pedagogical Knowledge (TPK) ability of educators is studied. social contact during this period. Further, 90% of them trying their best to enhance their teaching skills by the effective utilization of online teaching aids to make it as best as conventional pedagogical process and 10% of them reported that they have not utilized online teaching aids at all. © 2021, Rajarambapu Institute Of Technology. All rights reserved.