An Enhanced Multipath TCP: E-Adoption of Emerging Technology for Better Internet Bandwidth

Since 2020, the coronavirus disease 2019 (COVID-19) pandemic and lockdown policy have changed our life drastically. Due to this, companies, offices, schools, etc. are running in online mode. Therefore, the demand for internet bandwidth is very popular nowadays. Due to an increase in demand for internet bandwidth and the availability of multihomed devices, multipath TCP (MPTCP), and e-adoption of emerging technology enhanced bandwidth by utilizing the bandwidth of all available networks simultaneously. This paper analyzes the working principle of the MPTCP so that each internet device can easily use MPTCP to achieve high bandwidth. Load distribution and its performance mainly depend on the congestion control algorithm and the packet scheduler. MPTCP has various existing packet scheduling algorithms and congestion control algorithms. Here, the authors compare the performance of MPTCP with each congestion control algorithm and packet scheduler one by one and try to find out the best-performing MPTCP. This paper also shows that the MPTCP helps COVID-19 patients in various aspects.

Machine Learning-Based COVID-19 Classification Using E-Adopted CT Scans

In recent years, several machine learning models were successfully deployed in various fields. However, a huge quantity of data is required for training good machine learning. Data are distributivity stored across multiple sources and centralizing those data leads to privacy and security issues. To solve this problem, the proposed federated-based method works by exchanging the parameters of three locally trained machine learning models without compromising privacy. Each machine learning model uses the e-adoption of CT scans for improving their training knowledge. The CT scans are electronically transferred between various medical centers. Proper care is taken to prevent identify loss from the e-adopted data. To normalize the parameters, a novel weighting scheme is also exchanged along with the parameters. Thus, the global model is trained with more heterogeneous samples to increase performance. Based on the experiment, the proposed algorithm has obtained 89% of accuracy, which is 32% more than the existing machine learning models.

Machine Learning-Based COVID-19 Classification Using E-Adopted CT Scans

In recent years, several machine learning models were successfully deployed in various fields. However, a huge quantity of data is required for training good machine learning. Data are distributivity stored across multiple sources and centralizing those data leads to privacy and security issues. To solve this problem, the proposed federated-based method works by exchanging the parameters of three locally trained machine learning models without compromising privacy. Each machine learning model uses the e-adoption of CT scans for improving their training knowledge. The CT scans are electronically transferred between various medical centers. Proper care is taken to prevent identify loss from the e-adopted data. To normalize the parameters, a novel weighting scheme is also exchanged along with the parameters. Thus, the global model is trained with more heterogeneous samples to increase performance. Based on the experiment, the proposed algorithm has obtained 89% of accuracy, which is 32% more than the existing machine learning models.

Relevance of Duties in the Contemporary World: With Special Emphasis on Gandhian Thought

This book reflects on the significance of duties in creating an egalitarian society by collating and contextualizing the relevant literature. It particularly focuses on an appreciation of Gandhi's views on duty to showcase how they remain pertinent to create a cohesive, responsible and value-based society in the present right-dominated world. A viable solution to the current real world problems could be found in exploring the philosophy on duties and the book provides relevant literature in this regard. It undertakes jurisprudential analysis of duty in a rights-dominated world, identifying the gaps in realising the potential of duty to address the critical issues of the present times. It argues that enforcement of rights depends heavily on the observance of duties and proposes coherence in right-duty relationship. Gandhian thought on duty recognises duty as a precursor to rights and emphasises that the observance of duties guarantees the enforcement of rights. The relevance of duties and Gandhian thoughts on the same is not restricted to India but transcends borders with profound appeal. Gandhian thoughts have become even more relevant in the current times to examine the situation of COVID-19 pandemic, racial discrimination (BLM), environmental crises, digital divide, health care and medical care crises, refugee and migrant labour problems and it can offer promising solutions based on the nuances of social solidarity, self realisation of duties/responsibilities, local governance, compassion and humanity. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

Impact of COVID-19 on Import and Export of Petroleum Products and Crude Oil in India

Imports and export have a significant contribution to increasing the effect of economies of scale and industrialization and lead to an increase in foreign exchange earnings. The oil and gas industry is a prime factor of development in the Indian economy. The natural gas and petroleum sector of India contributes one-seventh percent of the South Asian countries. Petroleum products can be considered ranked among the top five contributors of export trade in India. With the spread of COVID-19 at an exponential rate leading to shut down of industries, manufacturing, transportation, and offices, it has widely impacted the global supply chain. This research aims at studying the effect of COVID-19 on the export and import volumes of petroleum products and crude oil in India. Along with that, the research also covers the changes observed in the consumption and production of petroleum products and domestic and international exchange rate of crude oil before and after the outbreak of COVID-19. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Patent and Pandemic: Exploring Duties, Obligations and Responsibilities

Patents are based on a delicate policy to promote technological progress by incentivising the inventor and enabling others to participate in the innovation process through public disclosure. Patent being a property does not fit in the rigid proprietary framework, given its goal to promote the public good. The limits to patent rights on one hand and duties and obligations on the other complement patent rights, enabling the system to promote social good. However, in practice, an aggressive assertion of patent rights often ignores the duties and obligations recognised under the patent system. The "exclusivity” of patents imposes a duty on third parties to respect the patentee's patent rights. However, while recognising the duties and obligations of the patentee, the patent systems put less emphasis on it in practice. Though limits to patent rights such as research exemptions, compulsory licences and governmental use are recognised statutorily and judicially, an appreciation of duties and obligations may produce a more pragmatic result. In the current pandemic situation, open and collaborative efforts such as Open COVID Pledge, non-assertion of exclusive rights on technologies and research tools assisting in the vaccine production reflect promising approaches. Nevertheless, the challenges as the accessibility and affordability of the potential vaccine are still on. Gandhi's perspective on trusteeship could be contextualised in the patent realm to promote a duty-based regime in tune with the broader goals of patent policy. Against this backdrop, the present chapter explores the edifice and relevance of duties and obligations under the patent system in the light of contemporary challenges. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

Creating a risk-free hospital environment for patients, healthcare workforce and visitors through technology

Patient healthcare and management has taken leaps and bounds in advancement with the myriad technological innovations available to us now. The COVID-19 pandemic, while initially a setback, proved to be a springboard for the adoption and adaptation of cutting-edge technology that is crucial to our survival as a species. Examples of such are MySejahtera, vaccine production, genomic studies, contact tracing devices, alternative and green modes of transportation, increasing use of contactless food delivery services, and many more. The main challenges to hospital service providers are to integrate digital healthcare technologies into traditional hospital services with the aim to create a transparent and highly efficient healthcare system without walls or barriers. Hospital executives should be planning on how to integrate technology into newly built facilities and retrofit older facilities to enable a seamless integration between all components in healthcare services. As a healthcare administrator, minimization of patient safety-related risks is my foremost priority. While the benefits of health information technology are legion and can be used to enhance patient safety to an unprecedented level, I believe we should proceed with caution to ensure that patient welfare is our utmost priority, whilst also upgrading our services alongside our healthcare technology. The spread of COVID-19 stretched healthcare operational systems to their limits not only in Malaysia, but worldwide as well. Shortages and shortfalls had to be swiftly addressed, and as the director of the main COVID-19 hospital, the speaker has had a wealth of experience optimizing and modernizing response mechanisms. The speaker will share examples of improvements made for crisis response during the peak of the COVID-19 pandemic, for example, centralized clinical command centers, hospital dashboards, virtual conferences, virtual learning, and many more. The speaker will also share some of the roles that a healthcare leader must focus on to prepare an organization for the adoption and use of future technology as well as readiness of organizational capabilities for long-term success. Technology for healthcare must be balanced by an appropriate level of human clinical expertise for final decision-making to ensure that patients receive high quality and safe care.

Reduction in environmental pollution due to lockdown in the COVID-19 pandemic: A case study of Delhi-NCR

The Indian government imposed a countrywide lockdown on 25 March 2020 to contain the COVID-19 virus. The lockdown has led to a tremendous economic loss because of the closing of all industries and other activities. However, it has brought a brighter side to environmental quality improvement. This study assesses the influence of lockdown on Delhi-NCR's air and water quality. The earth system rejuvenated during the lockdown. An effort is made to understand the water quality of the Yamuna River in Delhi and the air quality of the Delhi-National Capital Region (Delhi NCR) during the lockdown. In the Yamuna River surrounding Delhi, a reduction of 1-10%, 33-66%, 51%, 45-90%, and 33-82%, respectively, in pH, EC, DO, BOD, and COD has been observed compared to the pre-lockdown. Similarly, the particulate matter concentration reduced by 31-53% in PM10 and 22-48% in PM2.5 during the lockdown of2020 in comparison to the earlier years (2018 and 2019). Hence, the periodic lockdown has positively impacted the air and water quality in Delhi NCR. © 2021, IGI Global.

Covid'19 Vaccination Decision-Making Method and Subsystem Based on Civil Law

The conducted analysis of civil law grounds on the need and possibility of vaccination against Covid'19 in Ukraine made it possible to determine the categories of workers subject to compulsory vaccination, as well as a list of medical contraindications and warnings to vaccination against Covid'19. Developed Covid'19 vaccination decision-making method based on civil law provides: a conclusion on the mandatory or optional depending on the profession and place of work of the patient (but desirability) vaccination from Covid'19;conclusion on the possibility or contraindications to vaccination from Covid'19 - depending on the existing diseases and the current state of health of the patient;conclusion on the type of contraindication and its duration - in the case of a conclusion on contraindications to vaccination from Covid'19. Developed Covid'19 vaccination decision-making subsystem based on civil law provides a conclusion on whether or not vaccination from Covid'19 is mandatory or optional from the point of view of profession and place of work (but desirability);conclusion on the possibility or contraindications to vaccination from Covid'19;conclusion on the type of contraindication and its duration. So the subsystem will be useful for patients who, truthfully answering questions from the subsystem, will receive a conclusion on the need and possibility of vaccination from Covid'19 them or their relatives, as well as for family physicians, which will reduce the burden during patient counselling and make it easier to answer questions about the need and possibility of vaccination, as they will no longer need to know all the current legislation and civil law. Copyright © 2022 for this paper by its authors.

Amalgamation of IoT, ML, and Blockchain in the Healthcare Regime

Healthcare plays a critical role in the nation development and its economy. Recent Covid-19 pandemic has witnessed the importance of shifting the conventional healthcare infrastructure toward an automated environment that leverages the emerging paradigms such as Blockchain, Internet of Things (IoT), Machine Learning (ML), and Artificial Intelligence (AI). Further, through this chapter, we demonstrated several technologies which are effective and are essential step into future healthcare system. The amalgamation of these technologies will influence future course of healthcare environment which is pervasive and ubiquitous. This chapter explores such transition and opportunities that would bring the disruptive changes through emerging technologies providing connectivity and interaction among machines and humans for better clinical care irrespective of any ethnic or geographical boundaries. © 2021 Scrivener Publishing LLC.

‘WAIT’ … A Mobile App to Navigate and Assist Towards Polite and Effective Online Communication

This study illustrates the innovation of a mobile app named ‘WAIT’ developed for Android-based applications. Increasingly, most communication in current times is online, and this characteristic has been heightened due to restrictions caused by the Covid19 pandemic. During online communication, the art and etiquette of communication are often omitted. The researchers observed that online interactions tend to be careless and too quick with expressions of anger or just communication that is quick, resulting in sometimes inadvertent rude, abrupt and ambiguous communication. Hence, this app is designed to address this problem and assist users to use polite expressions in their online communication. The objectives of this app are to enable users to “wait”, think and refer to alternative ways how to begin, end and use specific keywords in response to various general situations, using polite expressions. This app is an easy-to-use mobile app. The researchers conducted a preliminary study with school and college students, whereby they were given an online survey with situations requiring a response before and after using the app. Additionally, online questionnaires were given to the participants after using the app. After using the app, the results showed positive feedback in polite and effective communication, leading to more harmony in online interactions and online society © 2022. International Journal of Interactive Mobile Technologies.All Rights Reserved.

When the doorbell rings in COVID-19 times: Numerical insights into some possible scenarios.

As ongoing Corona virus disease 2019 pandemic is ravaging the world, more and more people are following social distancing norms, avoiding unnecessary outings and preferring online shopping from the safety of their home over visiting brick and mortar stores and neighborhood shops. Although this has led to a significant reduction in chances of exposure, human-to-human interaction at the doorstep of the customer might be involved during the delivery of the ordered items. This human-to-human doorstep interaction arises in some other situations also. There is a finite probability that the person standing in front of the door coughs or sneezes during such an interaction. In this work, a three dimensional (3D) Euler-Lagrangian computational fluid dynamic model is used to understand the transmission and evaporation of micrometer-size droplets generated due to a coughing event in this setting. Different possible scenarios varying in wind direction, wind velocity, ventilation in the vicinity of door, and extent of door opening have been postulated and simulated. The results obtained from numerical simulations show that in the presence of wind, the dynamics of transmission of droplets is much faster than the dynamics of their evaporation. Thus wind velocity and direction have a significant impact on the fate of the droplets. The simulation results show that even if the door is opened by a very small degree, cough droplets enter through the door. Having open windows in the vicinity of the door on a windy day is expected to reduce the chance of the exposure significantly.

Using Susceptible-Exposed-Infectious-Recovered Model to Forecast Coronavirus Outbreak

The Coronavirus disease 2019 (COVID-19) outbreak was first discovered in Wuhan, China, and it has since spread to more than 200 countries. The World Health Organization proclaimed COVID-19 a public health emergency of international concern on January 30, 2020. Normally, a quickly spreading infection that could jeopardize the well-being of countless individuals requires prompt action to forestall the malady in a timely manner. COVID-19 is a major threat worldwide due to its ability to rapidly spread. No vaccines are yet available for COVID-19. The objective of this paper is to examine the worldwide COVID-19 pandemic, specifically studying Hubei Province, China;Taiwan;South Korea;Japan;and Italy, in terms of exposed, infected, recovered/deceased, original confirmed cases, and predict confirmed cases in specific countries by using the susceptible-exposed-infectious-recovered model to predict the future outbreak of COVID-19. We applied four differential equations to calculate the number of confirmed cases in each country, plotted them on a graph, and then applied polynomial regression with the logic of multiple linear regression to predict the further spread of the pandemic. We also compared the calculated and predicted cases of confirmed population and plotted them in the graph, where we could see that the lines of calculated and predicted cases do intersect with each other to give the perfect true results for the future spread of the virus. This study considered the cases from 22 January 2020 to 25 April 2020.

Diagnosis of COVID-19 from chest X-ray images using wavelets-based depthwise convolution network

Coronavirus disease 2019 also known as COVID-19 has become a pandemic. The disease is caused by a beta coronavirus called Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The severity of the disease can be understood by the massive number of deaths and affected patients globally. If the diagnosis is fast-paced, the disease can be controlled in a better manner. Laboratory tests are available for diagnosis, but they are bounded by available testing kits and time. The use of radiological examinations that comprise Computed Tomography (CT) can be used for the diagnosis of the disease. Specifically, chest X-Ray images can be analysed to identify the presence of COVID-19 in a patient. In this paper, an automated method for the diagnosis of COVID-19 from the chest X-Ray images is proposed. The method presents an improved depthwise convolution neural networkfor analysing the chest X-Ray images. Wavelet decomposition is applied to integrate multiresolution analysis in the network. The frequency sub-bands obtained from the input images are fed in the network for identifying the disease. The network is designed to predict the class of the input image as normal, viral pneumonia, and COVID-19. The predicted output from the model is combined with Grad-CAM visualization for diagnosis. A comparative study with the existing methods is also performed. The metrics like accuracy, sensitivity, and F1-measure are calculated for performance evaluation. The performance of the proposed method is better than the existing methodologies and thus can be used for the effective diagnosis of the disease. © 2018 Tsinghua University Press.