scholarly journals CNN-LSTM Model for Verifying Predictions of Covid-19 Cases

2020 ◽  
pp. 25-32
Author(s):  
Shawni Dutta ◽  
Samir Kumar Bandyopadhyay ◽  
Tai-Hoon Kim
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
World Health ◽  
Human Beings ◽  
Short Period ◽  
Machine Learning Approach ◽  
The World ◽  
Working Day ◽  
Health Organization ◽  
Near Future

COVID-19 disease came to earth in December 2019 in Wuhan. It is increasing exponentially throughout the world and affected an enormous number of human beings. The World Health Organization (WHO) on March 11, 2020 declared COVID-19 was characterized as “Pandemic”. Clinical Doctors have been working on it 24 hours in the entire world. These doctors are testing whether the particular human has been affected with the disease using testing kit and other related process. Researchers have been working day-night for developing vaccine for the disease. Since the rate of affected people is so high, it is difficult for clinical doctors to check such a large number of coronavirus detected humans within reasonable time. This paper attempts to use Machine Learning Approach to build up model which will help clinical doctors for verification of disease within short period of time and also the paper attempts to predict growth of the disease in near future in the world. Two models were used for achieving this purpose- One is based on Convolutional Neural Network model where as another one consists of Convolutional Neural Network and Recurrent Neural Network. These two models are evaluated and compared for verifying the predicted result with respect to the original one. Experimental results indicate that the combined CNN-LSTM approach outperforms well over the other model.

Convolutional Neural Network Based American Sign Language Static Hand Gesture Recognition

2019 ◽  
Vol 10 (3) ◽  
pp. 60-73 ◽  
Author(s):  
Ravinder Ahuja ◽  
Daksh Jain ◽  
Deepanshu Sachdeva ◽  
Archit Garg ◽  
Chirag Rajput
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
American Sign Language ◽  
Sign Language ◽  
Automated System ◽  
World Health ◽  
American Sign ◽  
Hand Gestures ◽  
The World ◽  
Health Organization

Communicating through hand gestures with each other is simply called the language of signs. It is an acceptable language for communication among deaf and dumb people in this society. The society of the deaf and dumb admits a lot of obstacles in day to day life in communicating with their acquaintances. The most recent study done by the World Health Organization reports that very large section (around 360 million folks) present in the world have hearing loss, i.e. 5.3% of the earth's total population. This gives us a need for the invention of an automated system which converts hand gestures into meaningful words and sentences. The Convolutional Neural Network (CNN) is used on 24 hand signals of American Sign Language in order to enhance the ease of communication. OpenCV was used in order to follow up on further execution techniques like image preprocessing. The results demonstrated that CNN has an accuracy of 99.7% utilizing the database found on kaggle.com.

scholarly journals Study on Convolutional Neural Network to Detect COVID-19 from Chest X-Rays

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Azher Uddin ◽  
Bayazid Talukder ◽  
Mohammad Monirujjaman Khan ◽  
Atef Zaguia
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Close Contact ◽  
World Health ◽  
Contact Tracing ◽  
X Rays ◽  
Health Crisis ◽  
Gastrointestinal Problems ◽  
The World ◽  
Health Organization

The world is facing a pandemic due to the coronavirus disease 2019 (COVID-19), named as per the World Health Organization. COVID-19 is caused by the virus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was initially discovered in late December 2019 in Wuhan, China. Later, the virus had spread throughout the world within a few months. COVID-19 has become a global health crisis because millions of people worldwide are affected by this fatal virus. Fever, dry cough, and gastrointestinal problems are the most common signs of COVID-19. The disease is highly contagious, and affected people can easily spread the virus to those with whom they have close contact. Thus, contact tracing is a suitable solution to prevent the virus from spreading. The method of identifying all persons with whom a COVID-19-affected patient has come into contact in the last 2 weeks is called contact tracing. This study presents an investigation of a convolutional neural network (CNN), which makes the test faster and more reliable, to detect COVID-19 from chest X-ray (CXR) images. Because there are many studies in this field, the designed model focuses on increasing the accuracy level and uses a transfer learning approach and a custom model. Pretrained deep CNN models, such as VGG16, InceptionV3, MobileNetV2, and ResNet50, have been used for deep feature extraction. The performance measurement in this study was based on classification accuracy. The results of this study indicate that deep learning can recognize SARS-CoV-2 from CXR images. The designed model provided 93% accuracy and 98% validation accuracy, and the pretrained customized models such as MobileNetV2 obtained 97% accuracy, InceptionV3 obtained 98%, and VGG16 obtained 98% accuracy, respectively. Among these models, InceptionV3 has recorded the highest accuracy.

scholarly journals Forecasting COVID-19 Transmission in India Using Deep Learning Models

2020 ◽  
Vol 10 (2) ◽  
pp. 2044-2055
Keyword(s):  
Transmission Rate ◽  
World Health ◽  
Similar Data ◽  
Slowing Down ◽  
Short Period ◽  
The World ◽  
Novel Coronavirus ◽  
Health Organization ◽  
Susceptible Populations ◽  
Near Future

In the past 6 months, the world has come to a standstill due to an escalation in the number of cases of COVID-19. COVID-19 is an infectious disease that was formerly called as 2019-nCoV or the novel Coronavirus 2019. COVID-19 first originated in Wuhan, China, in late December 2019, and subsequently, the World Health Organization declared it as a pandemic on 11th March, 2020. Lack of preparedness for the COVID-19 pandemic has put colossal stress on the healthcare systems of the world’s largest economies. In a short period, the disease has spread to an unexpected number of people due to its high transmission rate and doesn’t show a sign of slowing down in the near future. Estimating the rising number of cases via predictive modeling can help gauge the quantity of various medical amenities required for the treatment of patients as well as protective apparatus for essential workers and susceptible populations. In this paper, we have performed time series forecasting on the publicly available COVID-19 datasets of India using RNNs with LSTM and GRU. Additionally, we also employ the final models for analyzing similar data from different countries.

Dietary and living regimen of covid-19 with special reference to Ayurveda Varsha and Sharad Ritucharya

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 758-762
Author(s):  
Amit Biswas ◽  
KunalChandankhede
Keyword(s):  
Environmental Changes ◽  
World Health ◽  
Human Beings ◽  
Dietary Regimen ◽  
Global Pandemic ◽  
The World ◽  
Health Organization ◽  
Disease Free ◽  
Individual Disease ◽  
Morbid Conditions

Wuhan originated Covid-19 disease is caused by SARC-COV 2 virus. It is a contagious disease it spread all over the world. World health organization declared a global pandemic disease. In Covid-19 immunity plays an important role. In old age people or having other co-morbid conditions the mortality rate is more. Ayurveda has a big role in improved immunity or to intact immunity. The principle of Ayurveda is to keep individual swastha (diseases free). To maintain individual disease-free Ritucharya is one of the important subjects of Ayurveda. Aimed of study is to find out Ritucharya literature from the Ayurveda and modern research specifically Varsha and Sharad ritu. Ritucharya contains dietary regimen, living modification, common medicine, and contraindicated things those changing according to environmental change. Upcoming season in India is Varsha and Sharad ritu. Environmental changes are huge in this season and it directly affected human beings. So this study reveals property of ritu, dietary regimen, living modification, common medicine and contraindicated things in upcoming varsha and sharad ritu.

scholarly journals Deafening silence on a vital issue: The World Health Organization has ignored the sexuality of persons with disabilities

2018 ◽  
Vol 7 ◽  
Author(s):  
Christine Peta
Keyword(s):  
World Health Organization ◽  
Well Being ◽  
World Health ◽  
Human Beings ◽  
Persons With Disabilities ◽  
The Public ◽  
National Priority ◽  
Social Welfare System ◽  
The World ◽  
Health Organization

In 2016, the World Health Organization, through the Global Cooperation on Assistive Technology Initiative, issued the Priority Assistive Products List which is meant to be a guide to member states of the 50 assistive products needed for a basic health care and/or social welfare system; it is also a model from which nations can develop their national priority assistive products lists. The aim of this opinion paper is to share my views about the Priority Assistive Products List on the grounds that it makes no distinct mention of sexual assistive devices, yet research has indicated that sexuality is an area of great concern for persons with disabilities. In any case, sexuality forms a core part of being human, and it impacts on both the physical and mental well-being of all human beings. I conclude in part that, in its present format, the list perpetuates the myth that persons with disabilities are asexual beings who are innocent of sexual thoughts, feelings and experiences. The list also propagates the stereotype that sexuality is a sacred, private, bedroom matter that should be kept out of the public domain, to the detriment of the health and well-being of persons with disabilities.

scholarly journals COVID-19 in the International Year of Plant Health

2022 ◽  
Vol 39 (4) ◽  
Author(s):  
José Jorge Gutiérrez-Samperio
Keyword(s):  
Life Forms ◽  
Plant Health ◽  
World Health ◽  
Human Beings ◽  
Pests And Diseases ◽  
The Bible ◽  
United Nations General ◽  
The World ◽  
The Face ◽  
Health Organization

<p>Pests, in their broad sense, have played an important part in the history of humankind. We could say that humans, crops and pests have walked together through life. Codices, glyphs, paintings and countless ancient documents, including the Bible and the Koran, bear witness to this. Humanity has been attacked by its own diseases, but also by those that limit them from obtaining food and deteriorate the environment. COVID-19, which is now troubling us and was declared a pandemic by the World Health Organization in March of 2020, became a part of the list of experiences we have suffered in the past, with pests or epidemics that caused millions of deaths by diseases or famines. It is paradoxical that this health contingency occurs when the United Nations General Assembly, on December 20th, 2018, in its resolution A/RES/73/252 decides to declare 2020 the International Year of Plant Health in order to “highlight the importance of plant health to improve food security, protect the environment and biodiversity and boost economic development” according to the pronouncement by the FAO. For the first time, in an era with great technological and scientific breakthroughs, humanity was aware of its vulnerability against the inevitable evolution of life forms in the face of dilemmas global impact caused by human beings. Thus, the pest or parasite makes its own declaration of existential preeminence through SARS-CoV-2 to remind us that the health of humans or plants is the essence of life and its continuity. But perhaps absolute health is not enough. It is necessary to find a balance in a world overwhelmed by giving so much in return for almost nothing to everyone living on it. If the sensor of our anthropocentric intervention of the world is climate change, then biological chaos is a masterpiece. The reemergence of pests and diseases considered eradicated, or those of zoonotic origin that had never accompanied our existence is a surreal dystopia that we will never be able to deny again.</p>

scholarly journals Automatic Prediction of Meningioma Grade Image Based on Data Amplification and Improved Convolutional Neural Network

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Hong Zhu ◽  
Qianhao Fang ◽  
Hanzhi He ◽  
Junfeng Hu ◽  
Daihong Jiang ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
High Accuracy ◽  
World Health ◽  
Tumor Type ◽  
Grade Prediction ◽  
Health Organization ◽  
Deep Learning Model ◽  
The Brain

Meningioma is the second most commonly encountered tumor type in the brain. There are three grades of meningioma by the standards of the World Health Organization. Preoperative grade prediction of meningioma is extraordinarily important for clinical treatment planning and prognosis evaluation. In this paper, we present a new deep learning model for assisting automatic prediction of meningioma grades to reduce the recurrence of meningioma. Our model is based on an improved LeNet-5 model of convolutional neural network (CNN) and does not require the extraction of the diseased tissue, which can greatly enhance the efficiency. To address the issue of insufficient and unbalanced clinical data of meningioma images, we use an oversampling technique which allows us to considerably improve the accuracy of classification. Experiments on large clinical datasets show that our model can achieve quite high accuracy (i.e., as high as 83.33%) for the classification of meningioma images.

scholarly journals Fighting Strategies Against the Novel Coronavirus Pandemic: Impact on Global Economy

2020 ◽  
Vol 8 ◽  
Author(s):  
Bapi Gorain ◽  
Hira Choudhury ◽  
Nagashekhara Molugulu ◽  
Rajani B. Athawale ◽  
Prashant Kesharwani
Keyword(s):  
Disease Transmission ◽  
Global Economy ◽  
World Health ◽  
World Population ◽  
Mortality And Morbidity ◽  
Short Period ◽  
The World ◽  
Treatment Measures ◽  
Novel Coronavirus ◽  
Health Organization

Sudden outbreak of a new pathogen in numbers of pneumonic patients in Wuhan province during December 2019 has threatened the world population within a short period of its occurrence. This respiratory tract–isolated pathogen was initially named as novel coronavirus 2019 (nCoV-2019), but later termed as SARS-CoV-2. The rapid spreading of this infectious disease received the label of pandemic by the World Health Organization within 4 months of its occurrence, which still seeks continuous attention of the researchers to prevent the spread and for cure of the infected patients. The propagation of the disease has been recorded in 215 countries, with more than 25.5 million cases and a death toll of more than 0.85 million. Several measures are taken to control the disease transmission, and researchers are actively engaged in finding suitable therapeutics to effectively control the disease to minimize the mortality and morbidity rates. Several existing potential candidates were explored in the prevention and treatment of worsening condition of COVID-19 patients; however, none of the formulation has been approved for the treatment but used under medical supervision. In this article, a focus has been made to highlight on current epidemiology on the COVID-19 infection, clinical features, diagnosis, and transmission, with special emphasis on treatment measures of the disease at different stages of clinical research and the global economic influence due to this pandemic situation. Progress in the development on vaccine against COVID-19 has also been explored as important measures to immunize people. Moreover, this article is expected to provide information to the researchers, who are constantly combating in the management against this outbreak.

Protecting health from metal exposures in drinking water

2016 ◽  
Vol 31 (1) ◽  
Author(s):  
Margaret-Ann Armour
Keyword(s):  
Drinking Water ◽  
World Health Organization ◽  
World Health ◽  
Human Beings ◽  
Environmental Determinant ◽  
The World ◽  
Health Organization

AbstractDrinking water is essential to us as human beings. According to the World Health Organization “The quality of drinking-water is a powerful environmental determinant of health” (

scholarly journals Evaluation of the Economic, Environmental, and Social Impacts of the COVID-19 Pandemic on the Japanese Tourism Industry

2020 ◽  
Vol 12 (24) ◽  
pp. 10302 ◽  
Author(s):  
Yusuke Kitamura ◽  
Selim Karkour ◽  
Yuki Ichisugi ◽  
Norihiro Itsubo
Keyword(s):  
Ghg Emissions ◽  
Climate Change Impacts ◽  
Social Impacts ◽  
Tourism Industry ◽  
World Health ◽  
Input Output ◽  
Short Period ◽  
The World ◽  
Table Analysis ◽  
Health Organization

According to the United Nations Environment Program (UNEP) annual Emissions Gap Report 2019, further reductions in greenhouse gas (GHG) emissions are needed to reduce climate change impacts. In Japan, the 2030 Intended Nationally Determined Contribution (INDC) target is an emissions reduction of 26% compared to 2013. The World Health Organization (WHO) declared that the coronavirus (COVID-19) outbreak has led to 43,341,451 confirmed cases and 1,157,509 confirmed deaths globally and affected 218 countries (as of 27 October 2020). In Japan, as of the same date, 96,948 infectious cases and 1724 deaths related to the new coronavirus had been recorded. These numbers continue to increase. In Japan, in March 2020, the number of international tourist arrivals decreased by about 93% compared to last year at the same period. The World Tourism Organization (UNWTO) reported several significant scenarios for the tourism industry. COVID-19 is the greatest shock to international tourism since 1950 and represents an abrupt end to the 10-year period of sustained growth that followed the 2009 financial crisis. It was thought that it would be possible to analyze the economic, environmental, and social impacts of rapid social changes. Thus, this study estimates changes in Japan’s tourist consumption, the carbon footprint (CFP), and employment due to the influence of the COVID-19 pandemic. The calculations in this study adopt a lifecycle approach using input–output tables. Based on these observations, this study uses four scenarios (SR 1, no recovery until December; SR 2, recovery from October; SR 3, recovery from July or September; and SR 0, same growth rate as 2018–2019) for Japan to calculate the CFP and employment change using input–output table analysis based on tourist consumption, which is a tourism metric. According to our results (2019 vs. SR 1 and 3), the consumption loss is between 20,540 billion yen (−65.1%) and 12,704 billion yen (−39.1%), the CFP reduction is between 89,488 Mt-CO2eq (−64.2%) and 54,030 Mt-CO2eq (−37.5%), and the employment loss is between 2,677,000 people (−64.2%) and 1,678,000 people (−37.5%). As of November 2020, the tourism industry continues to be affected by the COVID-19 pandemic. In the post-COVID-19 society, it will be necessary to maintain the GHG emissions reductions achieved in this short period and realize economic recovery. This recovery must also be sustainable for tourism stakeholders and society.

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