International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management最新文献

The pandemic of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is spreading all over the world. Medical health care systems are in urgent need to diagnose this pandemic with the support of new emerging technologies like artificial intelligence (AI), internet of things (IoT) and Big Data System. In this dichotomy study, we divide our research in two ways-firstly, the review of literature is carried out on databases of Elsevier, Google Scholar, Scopus, PubMed and Wiley Online using keywords Coronavirus, Covid-19, artificial intelligence on Covid-19, Coronavirus 2019 and collected the latest information about Covid-19. Possible applications are identified from the same to enhance the future research. We have found various databases, websites and dashboards working on real time extraction of Covid-19 data. This will be conducive for future research to easily locate the available information. Secondly, we designed a nested ensemble model using deep learning methods based on long short term memory (LSTM). Proposed Deep-LSTM ensemble model is evaluated on intensive care Covid-19 confirmed and death cases of India with different classification metrics such as accuracy, precision, recall, f-measure and mean absolute percentage error. Medical healthcare facilities are boosted with the intervention of AI as it can mimic human intelligence. Contactless treatment is possible only with the help of AI assisted automated health care systems. Furthermore, remote location self treatment is one of the key benefits provided by AI based systems.

At this time, COVID-2019 is spreading its foot in the form of a huge epidemic for the world. This epidemic is spreading its foot very fast in India too. One of the World Health Organization states that COVID-2019 is a serious disease that spreads from one person to another at very fast speed through contact routes and respiratory drops. On this day, India and the world should rise to an effective step to analyze this disease and eliminate the effects of this epidemic. In this paper presented, the growing database of COVID-2019 has been analyzed from March 1, 2020, to April 11, 2020, and the next one is predicted for the number of patients suffering from the rising COVID-2019. Different regression analysis models have been utilized for data analysis of COVID-2019 of India based on data stored by Kaggle in between 1 March 2020 to 11 April 2020. In this study, we have been utilized six regression analysis based models namely quadratic, third degree, fourth degree, fifth degree, sixth degree, and exponential polynomial respectively for the COVID-2019 dataset. We have calculated the root mean square of these six regression analysis models. In these six models, the root mean square error of sixth degree polynomial is very less in compared other like quadratic, third degree, fourth degree, fifth degree, and exponential polynomial. Therefore the sixth degree polynomial regression model is very good models for forecasting the next 6 days for COVID-2019 data analysis in India. In this study, we have found that the sixth degree polynomial regression models will help Indian doctors and the Government in preparing their plans in the next 7 days. Based on further regression analysis study, this model can be tuned for forecasting over long term intervals.

[This corrects the article DOI: 10.1007/s41870-020-00504-x.].

Coronavirus disease 2019 (COVID-19) is the name given by the World Health Organization (WHO) to the highly contagious and infectious disease caused by the Novel Corona Virus or SARS-CoV-2, which was first reported on 31 December 2019 in Wuhan city of the capital of China's Hubei province. Due to the rapid increase in the number of infections worldwide, the WHO in March 2020, declared COVID-19 as a pandemic. Historically, first coronavirus had surfaced in 1965 with symptoms of common cold. Since then five different strands of this virus have emerged, most lethal of them was the Severe Acute Respiratory Syndrome (SARS), which infected about eight thousand people, killing ten percent of them. The COVID-19 is not the most deadly pandemic world has ever witnessed as the Spanish influenza pandemic, during 1918-19, killed more than fifty million people. Indeed COVID-19 has turned out to be the most lethal of all coronaviruses as it has infected at least three million people killing more than two hundred thousands of them in the first 4 months of its spread. Many politicians and social scientists have dubbed the depression, being caused by COVID-19, worse than that caused by the Second World War. In this article, we shall analyze economic, social, cultural, educational and political impact of the COVID-19.

Technology advancements have a rapid effect on every field of life, be it medical field or any other field. Artificial intelligence has shown the promising results in health care through its decision making by analysing the data. COVID-19 has affected more than 100 countries in a matter of no time. People all over the world are vulnerable to its consequences in future. It is imperative to develop a control system that will detect the coronavirus. One of the solution to control the current havoc can be the diagnosis of disease with the help of various AI tools. In this paper, we classified textual clinical reports into four classes by using classical and ensemble machine learning algorithms. Feature engineering was performed using techniques like Term frequency/inverse document frequency (TF/IDF), Bag of words (BOW) and report length. These features were supplied to traditional and ensemble machine learning classifiers. Logistic regression and Multinomial Naïve Bayes showed better results than other ML algorithms by having 96.2% testing accuracy. In future recurrent neural network can be used for better accuracy.

During the first 15 years of this century, seven thousand people have been crushed to death in stampedes. Many would argue that these fatalities could have been prevented by better control and management. Crowd management today needs to minimise the chances of occurrence of stampedes, fires and other disasters and also to deal with the ongoing threat of terrorism and outbreak of communicable diseases like EBOLA, HIV Aids, Swine Influenza H1N1, H1N2, various strands of flu, Severe Acute Respiratory Syndrome (SARS) and Middle Eastern Respiratory Syndrome (MERS). These challenges have created a need for using all available resources, especially modern tools and technology, when dealing with crowds. Radio Frequency Identification (RFID), which is already benefiting many industrial and government organisations around the world, may be useful for scanning crowded locations and hence in helping to prevent overcrowding. Other wireless technologies should also be considered for possible use in crowded events. Ideally, some of the regular crowded event locations should be transformed into smart cities. In this article we shall discuss different kinds of crowds and technologies for their management. In particular, we shall analyse cases where wireless and mobile technologies can be utilised effectively. The Hajj, which has witnessed several stampedes, is chosen as the case study but most of our findings would be applicable in other events like the Kumbh Mela.

Twenty first century has witnessed emergence of some ground breaking information technologies that have revolutionised our way of life. The revolution began late in 20th century with the arrival of internet in 1995, which has given rise to methods, tools and gadgets having astonishing applications in all academic disciplines and business sectors. In this article we shall provide a design of a 'spider robot' which may be used for efficient cleaning of deadly viruses. In addition, we shall examine some of the emerging technologies which are causing remarkable breakthroughs and improvements which were inconceivable earlier. In particular we shall look at the technologies and tools associated with the Internet of Things (IoT), Blockchain, Artificial Intelligence, Sensor Networks and Social Media. We shall analyse capabilities and business value of these technologies and tools. As we recognise, most technologies, after completing their commercial journey, are utilised by the business world in physical as well as in the virtual marketing environments. We shall also look at the social impact of some of these technologies and tools.

Healthcare management is currently undergoing substantial changes, and reshaping our perception of the medical field. One spectrum is that of the considerable changes that we see in surgical machines and equipment, and the way the procedures are performed. Computing power, Internet and associated technologies are transforming surgical operations into model based procedures. The other spectrum is the management side of healthcare, which is equally critical to the medical profession. In particular, recent advances in the field of Information Technology (IT) is assisting in better management of health appointments and record management. With the proliferation of IT and management, data is now playing a vital role in diagnostics, drug administration and management of healthcare services. With the advancement in data processing, large amounts of medical data collected by medical centres and providers, can now be mined and analysed to assist in planning and making appropriate decisions. In this article, we shall provide an overview of the role of IT that have been reshaping the healthcare management, hospital, health profession and industry.