Data Visualization for Corona Patients Globally using Real-Time APIs

All the nations' administrative units are concerned about the COVID-19 outbreak in different regions of the world. India is also trying to control the spread of the virus with strict measures and has managed to slow down its growth rate. The administration of each country faces the challenge of maintaining records of corona patients. To address this challenge, this work builds a website from scratch using real-time APIs for data visualization. The website provides information on the number of active cases, death cases, recovery cases, and total cases of COVID-19 patients in each country. The data can be visualized using graphs, making it easier to compare the situation in different countries. The website allows for monitoring which country has a higher number of deaths, patients, favorable recovery rates, and a large number of active cases. The COVID-19 status regarding patients can be analyzed through graphical representation using real-time data. © 2023 IEEE.

PSSO: Political Squirrel Search Optimizer-Driven Deep Learning for Severity Level Detection and Classification of Lung Cancer

Lung cancer accounts for about 7.6 million deaths annually worldwide. Early identification of lung cancer is essential for reducing preventable deaths. In this paper, we developed a Political Squirrel Search Optimization (PSSO)-based deep learning scheme for efficacious lung cancer recognition and classification. We used Spine General Adversarial Network (Spine GAN) to segment lung lobe regions where a Deep Neuro Fuzzy Network (DNFN) classifier forecasts cancerous areas. A Deep Residual Network (DRN) is also used to determine the various cancer severity levels. The Political Optimizer (PO) and Squirrel Search Algorithm (SSA) were combined to create the newly announced PSSO method. Experimental outcomes are assessed using the dataset of images from the Lung Image Database Consortium.

Learning impact of recent ICT advances based on virtual reality IoT sensors in a metaverse environment

Avatars of real individuals can be found all around the Metaverse. It has been nicknamed the "next big bang” for the Indian EdTech market, which some experts predict will reach $30 billion by 2032. Technology permeates 21st-century education, whether it is through academic programming, hands-on technical instruction, or concepts taught in classrooms and institutions. Virtual reality in the Indian educational system is still a topic of study. There isn't much research on virtual reality in education. Since women are now actively functioning as leaders and outperforming men in many spheres of life worldwide, women's empowerment is India's most powerful tool for growth. The lady governors and the countries led by these incredible women are bearing the load and pushing on alone in the struggle wherever it is needed, while the entire world holds its breath and prays every day for an unbelievable escape from the COVID-19 pandemic. Various non-governmental organizations (NGOs) seek to improve women's lives and provide them with self-sufficiency training. The government is likewise concerned about this issue and has established a number of programs to assist women. Information and communication technology (ICT) is significant in this context. ICT has improved the security, knowledge, education, employability, confidence, and popularity of women. The significance of ICT for the empowerment of women is highlighted in this study. To illuminate the various facets of ICT's impact on society, various examples have been addressed. Because of ICT, new generations of women all over the globe have defied all expectations and proven themselves in every aspect of life, even the most complicated and time-consuming realm of enterprise. In this regard, ICT may possibly become a magic wand for improving women's current situations. In this research, the eight factors that influence how ICT affects rural women's empowerment were found.

Role of digital twin technology in medical sector-Toward ensuring safe healthcare

In today's scenario, digital technology is gaining prominence in different sectors like business, healthcare, education, security, aerospace, construction, automotive, etc. Digital twin technology is a novel technology. It represents virtually physical objects or process. The basic building block of a digital twin is internet of things (IoT) and the goal of digital twin technology is to create, test, and validate in the virtual environment. In the perspective of the healthcare sector, the digital twin virtually represents physical entity or process. The chapter organization is as follows: introduction to digital twin technology, generic applications of the digital twin, the role of digital twin technology in healthcare, and finally, the conclusion. © 2023 Scrivener Publishing LLC.

Digital Service Quality from Elderly Generation Perspective to Improve Online Business and Economy: A Theoretical Framework

During the current COVID-19 pandemic, older people are encouraged to use information, communication and technology in their everyday lives and discouraged from physical interactions. In Malaysia, it shows that implementing the Movement Control Order (MCO) to control the spread of the COVID-19 pandemic saw a shift in consumer trends, prompting businesses to explore new strategies to interact with consumers. But there is no study indicating the contributions of older people in this new business environment. Several complaints were reported regarding the usability, acceptability, and suitability of these applications for the elderly. The objectives of this study: (1) to investigate issues and challenges on older citizens in current software design quality;(2) To identify current practises on software usage amongst the older citizens, especially in e-commerce and e-business applications;and (3) To propose a model a software design quality that meets older people requirements, limitations, and expectations. The new model helps the developers design and construct software compatible with the elderly based on a quality perspective. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Effect of yoga mudras in improving the health of users: A precautionary measure practice in daily life for resisting the deadly COVID-19 disease

COVID-19 is a deadly disease that affected millions of people around the world. Vaccines are presently being made available for curtailing the disease. However, many people lost their lives because of breathing problems associated with the virus infection. Science and technology have advanced a lot in the identification of the COVID-19 virus through RT-PCR tests and CT imaging. The ashtanga yoga focuses on the moral, intellectual, and health aspect improvement of individuals. This study notes that the role of Yoga (mudras) is inevitable in improving the health conditions of both the infected and noninfected persons. The effects of mudras in health care were scientifically proven, and many reputed works are there highlighting the merits of mudras. To this end, this research work proposed a set of mudras with a breathing exercise that focuses on the improvement of immunity and minimizes respiratory issues. A consistent practice of mudras with a breathing exercise for 30min each (morning and evening) paves the way toward a healthy life. The breathing exercise proposed in this research work is Nadi Shuddi Pranayama in Virasana position and the following mudras: garuda mudra, aswini mudra, adhi mudra, prana mudra, bronchial mudra, and apana vayu mudra. The chapter comprises of the following: introduction to yoga and its scientific evidence in improving health care, related works in improving health care by mudras, and a universal practice system comprising of breathing exercise and mudras for resisting COVID-19. In theory, the outcome of this chapter focuses on the holistic improvement of health care of people particularly during crises such as the COVID-19 pandemic. © 2022 Elsevier Inc. All rights reserved.

Medical Image Encryption using Latin Image Cipher Algorithm

Image processing has significant applications in the health care sector, medical data processing, analysis, storage, and transfer. The Latin Image Cipher algorithm was proposed in this work for the encryption of medical images. The encryption algorithm proposed in this research work comprises Latin square whitening, substitution, and permutation. The efficiency of the algorithm was also validated by inducing noise in the input images. The performance validation of the proposed algorithm was validated by the histogram analysis and correlation analysis. The information entropy measure also validates the proficiency of the encryption/decryption algorithm. The algorithm was developed on MATLAB 20021 and tested on COVID 19 CT images.

Forecast the death and recovery rate of COVID 2019 using ARIMA and PROPHET models

Because of the worldwide ongoing situation triggered by the Coronavirus (COVID-19) pandemic, millions of people lost their lives and the economic disturbances, globally billions of people have been directly or indirectly affected. In order to prevent deaths, it is of utmost importance to determine anticipated infected cases and the spread rate of the virus for advance planning to eliminate fatalities in healthcare. Even though vaccination started over the globe, different people had a different perception regarding the vaccination, so preferable solution to fight against it is, by following precautions and by creating awareness about Coronavirus, In rural areas and even in urban areas there is a lot of panic situations among people, to overcome panic situations, we proposed a model that uses the ARIMA model to forecast nCOVID-2019, and where we will show the death and recovery rate of nCOVID-2019 and also provided prevention and precaution tips to follow. We designed a user-friendly web interface that displays the recovery rate and death rate ratio and can help us to free ourselves from the panic situation. The aim of this paper is to evaluate time series relevant data for the top ten COVID-19 significantly impacted nations to forecast the spread of the epidemic. © 2022 Author(s).

Non Linear Tensor Diffusion Based Unsharp Masking for Filtering of COVID-19 CT Images

COVID-19 is a dreadful disease caused by coronavirus and it belongs to the family of single-stranded RNA viruses. The Computed Tomography (CT) imaging was found to be a primary diagnostic tool in the screening of COVID-19. Preprocessing is the first stage in image processing operation, it improves segmentation and classification accuracy and hence it gains importance. Preprocessing techniques plays vital role in the improvement of image quality and the objective is to minimize noise, elimination of artifacts and aliasing effects. The improved contrast aids image segmentation and compression algorithms for better diagnosis by physicians. The CT images in general are corrupted by Gaussian and salt and pepper noise. The classical filtering techniques are median, Gaussian, bilateral and anisotropic diffusion. This chapter proposes a novel filtering technique, Non Linear Tensor Diffusion based Unsharp Masking for CT images. The performance validation was done by performance metrics like Just Noticeable Distortion (JND), Discrete Entropy (DE) and average mean brightness error (AMBE) for comparative analysis, classical filtering algorithms are used. The filtering algorithms are implemented in Matlab2015b and tested on real time CT images of COVID-19. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.