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Since its original announcement in Wuhan, the (COVID-19) has become a well-known medical illness in China and around the world. The plague has wreaked social and economic outcomes all over the world. The increased number of COVID-19 testing provides additional information about the pestilence's spread, potentially allowing our environmental factors to prevent future pollution wearing a facial covering that prevents flying beads, maintaining sufficient separation between individuals, and limiting close contact can all help to combat the outbreak. Hence, this examination paper centers on utilizing As an implanted vision framework, the Face Mask, and the Social Distance Discovery concept are used. Individuals who were found disregarding the local area or not wearing a veil were found. After making and eliminating the models, the anointed one got 100 percent certainty focuses. This paper gives a relative investigation of facial recognition and facial veiling models. Framework execution is tried for precision, memory, F1 focuses, and support. [ABSTRACT FROM AUTHOR]

WeChat is the most popular social media in the world, especially in China. There is no overview of publications in the area of WeChat Research which shows the big picture using data from all countries. This paper aims to review the status and visual map position of WeChat publication indexed by Scopus used a Bibliometric. The research was carried out using Bibliometric techniques. Data analysis as well as visualization utilizing VOS Viewer program and the Scopus function for analyze search results. In this review, the details collected applied to 1.264 documents issued from 2012 through 2019. The study reveals that He, L. and Sun Yat-Sen University were the most active individual scientists and affiliated institutions in WeChat Research. In WeChat Research, the Computer Science and Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes In Bioinformatics were the most areas of study and dissemination sources. There were three worldwide group maps with collaborative researchers. In order to identify the body of knowledge created from seven years of publication, this study constructed a convergence axis grouping comprising of WeChat Research: Social Networking, Education, Human, Article, WeChat. abbreviated as the SEHAW theme. [ABSTRACT FROM AUTHOR]

In 2019, the world witnessed a rapid spread of the Coronavirus (COVID-19) disease in one of China's cities, Wuhan. The disease was announced in December 2019 to be a springboard for the whole world, where most countries were infected with it. It greatly affected the health of society and became a real danger to humans. Therefore, it is necessary to diagnose the infected people and quarantine them to combat this pandemic and limit its spread. This paper aims to give a review of COVID-19 diagnosis methods. According to the diagnostic methods, the previous works are classified into two categories for diagnosing Coronavirus; X-ray and Computed Tomography (CT)-Scan. Artificial intelligence (AI) is used to improve the diagnosis accuracy of the presented methods. On this basis, automated diagnostic tools have been developed that distinguish people infected with the Coronavirus from other diseases. Moreover, the performance parameters of the previous studies were compared in terms of diagnosis method, adopted algorithm, diagnosis accuracy, sensitivity, and specificity. Furthermore, the challenges and limitations of the existing methods for diagnosing Coronavirus were explored. AI has proven to be a reliable way to diagnose the spread of the epidemic through advanced algorithms based on blind and machine learning, especially the convolutional neural network (CNN), which plays a vital role in extracting sensitivity, specificity, and accuracy. [ABSTRACT FROM AUTHOR]

The motor base is one of the most important parts in the three-axis drive system of high-grade precision machine tools. Its machining accuracy has a great influence on the positioning accuracy and repeated positioning accuracy of the machine tools. In this paper, by optimizing the processing technology, designing the special tooling, adjusting the processing procedure, replacing the traditional horizontal processing sequence with the vertical processing sequence, the parts processing with high quality, high efficiency and low cost is realized, and the consistency of important dimensions is guaranteed. Through process research and Intelligent NC machine tool processing, the analysis and automatic management of parts processing data are effectively realized. At the same time, the group processing technology is adopted, so that the processing cost can be greatly reduced. Therefore, the manufacturing method of motor base mentioned in this paper has reached the advanced level in China, and has a wide promotion significance. [ABSTRACT FROM AUTHOR]

The world is going through a very hard time due to the pandemic first reported on December 2019 at Wuhan China. Vaccination process has started in different corner of world in war foot zone, still new cased are reported every day. 48 million people have already died out of this virus infection in the world. [1]. The disease caused by novel coronal virus needs to be detected at a very early stage and if proper care taken patient will survive. With Artificial Intelligence and Machine learning advancement it is possible to detect disease by analyzing symptoms. We have proposed a model to predict COVID 19 using Baggingensemble mechanism with Gaussian Naïve Bayes as base learner. [ABSTRACT FROM AUTHOR]

Corona virus or COVID-19 has taken the world by storm. In December 2019 while the world was looking forward to 2020, news broke about an outbreak of a virus thought to be less deadly than SARS and Ebola from China. It started as an isolated case in Wuhan, a province in China, gradually became a global pandemic, spreading across continents and invading countries with devastating effect. As someone rightly said "Globalization also means there are no boundaries for disease!". It spread to around 190 UN countries out of 195. The main source for spread of the virus is due to close proximity droplets during respiration when people cough or sneeze. Although these droplets might be formed during inhalation but the virus is not considered carried by the wind. So the possible way of stopping this pandemic to further be destructive was to break the chain. Therefore, we need to study the approaches followed by various countries to secure this prospect. But as this would not be efficient to analyze all countries approaches, we would be focusing on 3 major countries going through worst scenarios – China, Italy and England. This study could help developing countries to go for such measures in order to save their people while benefitting from the advanced technological inventions in fields of AI and ML, Data Science. [ABSTRACT FROM AUTHOR]

Waste management is a major duty for the government to handle, because cities must be clean, beautiful, and sanitary for a country to grow. According to estimates, India produces 62 million tonnes of waste every year, making it the world's second most populous metropolis behind China. However, because of the massive scale mixing of the waste, it is a difficult and costly procedure to separate in the final stages. Of the total 62 million tonnes of rubbish, 5.6 million tonnes are plastic waste. As we all know, plastic can be readily recycled, and if plastic is put on Earth/landfills, it poses a severe issue of global warming. For proper recycling process and to provide a cleaner, safer, and more sanitary workplace, as well as increased operational efficiency while lowering management costs and resources segregation of the garbage a Smart way of garbage management with help of modern cutting-edge technologies like Artificial Intelligence and Internet of things should be done. So, in the current work a system which automatically segregates the waste using image processing and Waste/trash is divided into bins provided beneath the conveyer utilising a conveyer system is proposed. Machine Learning and Deep Learning are subsets of Artificial Intelligence using ML and DL we can efficiently segregate trash using camera module and separate them into bins/chambers. And using Internet of things we can remotely control the trash inside the bins with help of readings from ultrasonic sensors inserted, once the trash is above the threshold, we can notify the respected cleaning department which prevents the overflow of the trash. [ABSTRACT FROM AUTHOR]

COVID-19 is a respiratory illness caused by the SARS-CoV-2 (Corona Virus), which first appeared in December of the year 2019. Covid-19 evolved from Corona Virus is a severe acute respiratory illness. Wuhan, Hubei, China and resulted in an ongoing pandemic. COVID-19, which was triggered by the SARS-CoV-2 virus, has rapid global dissemination, leading to worldwide flare ups. To lessen it's spread and safe communication it is necessary to develop speedy and contactless solutions in combat against it. The current gold standard for establishing its identification is RT-PCR Tests. This method of testing, however, is costly, time-consuming, and exceeds the social distance. Likewise, as pandemic is required to remain for some time, there is need for another analysis apparatus which beats these impediments, and is deployable at an enormous scope. The essential symptoms for this virus include cough and breathing challenges. Using AI and AI methods we can analyze respiratory sound which can give helpful insights, enabling the design of diagnostic tools. This survey uses AI based ML and DL approaches to offer a thorough overview of the COVID-19 diagnosis and therapy by analysing breathing patterns. [ABSTRACT FROM AUTHOR]

The very rapid development of technology today cannot be separated from the role of artificial intelligence. Artificial intelligence is a thought process or intelligence like humans' that machines can use to do specific jobs. The use of artificial intelligence is very diverse in various fields, including the health sector. Recently the world's media has been shocked by the virus spread in China, namely the coronavirus. Corona can cause severe pneumonia for sufferers. Pneumonia itself is inflammation of the lungs caused by a virus. One of pneumonia sufferers' characteristics is that there is a fluid that looks like white spots on radiology or chest X-rays. However, it will be challenging to diagnose because at a glance, the radiological test results of lungs with pneumonia and normal lungs are similar. So, misdiagnosis is possible. Therefore, this study aims to create a machine learning model to classify lungs with pneumonia and normal lung on chest radiological images using the Convolutional Neural Network (CNN) algorithm. CNN is well known as a method in which the data process both image and video. The classification obtained for validation results in an accuracy value of 94%-99% for the pneumonia category, which suggests that the model can predict the image correctly. Meanwhile, for normal lung images, the accuracy rate is 84% -98%. This shows that the model can predict almost all of the images well; there is only one image that is not predicted correctly. [ABSTRACT FROM AUTHOR]