ABSTRACT
The present global situation of COVID-19 pandemic has broke through regional, revolutionary, philosophical, spiritual, social, and educational barriers. By utilizing an interconnection of network, an Internet of Things enabled medical system is useful for regular monitoring of COVID-19 patients. It also aids in improving patient experience and reducing re-hospitalizations. The arrival of the IoT has effect on reducing healthcare costs and enhancing the treatment outcome of affected patients. As a result, the goal of this study is to analyze and emphasize the overall applicability of the well-established IoT concept by providing a conceptual outlay to combat the COVID-19 pandemic. © 2023 Author(s).
ABSTRACT
Crude oil is an imperative energy source for the global economy. The future value of crude oil is challenging to anticipate due to its nonstationarity in nature. The focus of this research is to appraise the explosive behavior of crude oil during 2007-2022, including the most recent influential crisis COVID-19 pandemic, to forecast its prices. The crude oil price forecasts by the traditional econometric ARIMA model were compared with modern Artificial Intelligence (AI)-based Long Short-Term Memory Networks (ALSTM). Root mean square error (RMSE) and mean average percent error (MAPE) values have been used to evaluate the accuracy of such approaches. The results showed that the ALSTM model performs better than the traditional econometric ARIMA forecast model while predicting crude oil opening price on the next working day. Crude oil investors can effectively use this as an intraday trading model and more accurately predict the next working day opening price.
ABSTRACT
The pandemic turned life upside down, including causing unavailability and an inability to access rehabilitation in the hospital. However, the need to be fit and healed does not stop, so rehabilitation innovation from the digital sectors plays a role in approaching the patient, as the patient requires a medical professional to be healed. Rehabilitation via a digital pathway is fraught with difficulties, but advances in technology and research have enabled it to be used to the greatest extent possible in this disaster. Digital health has increased its efficacy in response to the pandemic, as it is now available in developing countries where there is an inability to visit a clinic for rehabilitation, and now the rehabilitation tool is accessible to the patients in their hands and they can connect to their therapist at any time. The rehabilitation is designed based on the patient's illness, feedback, and health data stored on the application devices, which regulate and provide feedback from both sides, from the patient and other improvement changes gathered with the help of digital applications. Digital health allows for online consultation, assessment, and 24-h monitoring, all of which are directly shared with the rehabilitation team. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
ABSTRACT
With the detection of Omicron, a new variant of severe acute respiratory syndrome coronavirus-2 in South Africa, a question arises regarding its implication in public health. The infectivity, ability of getting detected by available testing method and effectiveness of existing vaccine against this strain are not known properly. This Omicron variant can impact public health similarly or more than the Delta variant. The research is going on in many countries to get conclusion regarding the impact of the Omicron variant in public health.
ABSTRACT
Introduction: Coronavirus Disease-2019 (COVID-19) pandemic has made a huge impact on medical education resulting in adoption of online methods of teaching in order to continue with the process of teaching and learning so as to complete the syllabus. In addition, online education methods also helped to provide psychological support to the students in this time of crisis. Aim: To evaluate the perception of students for online learning and to compare it with conventional classroom teaching. Materials and Methods: This cross-sectional study was conducted in the Department of Pharmacology at Mahatma Gandhi Medical College and Hospital, Jaipur, Rajasthan, India, on fifth semester 148 medical undergraduates, in April, 2021. All the participants were randomly divided into two groups, with each group consisting of 74 students. Group I was taught antitubercular drugs through online method while, Group II was taught the same topic in classroom and then a cross-over was done among the 2 groups for antimalarial drugs on the second day. The perception of students towards online learning and the preferred method of teaching were evaluated using a predesigned standardised questionnaire. The collected data was analysed using Z-Test and p-value 0.05 was considered significant. Results: Out of 148 students, 62.84% were females. Mobile phones (86.48%) were the most commonly used gadgets for online learning. Majority of students preferred conventional classroom teaching with regard to convenience (75.67%), acquisition of knowledge (83.78%), practical skills (89.86%), interactive (84.45%), doubt clearance and the preferred method of teaching (81.08%). However, most of the students agreed that online learning saves time (62.83%) and was better suited for submission of assignments (68.9%). A statistically significant difference (p-value 0.05) was observed when online learning was compared with classroom teaching. Conclusion: The study concluded that online learning is not a substitute for classroom teaching but might supplement conventional classroom teaching. However, it helps in completion of syllabus and boosts the morale of the students during this pandemic.
ABSTRACT
The unprecedented outbreak of the 2019 novel coronavirus, termed as COVID-19 has brought new techniques/technologies which are emerging a lot in today’s research industry including 5G, Internet-of-Things (IoT), Edge Computing, Blockchain, etc., to more light. This is attracting more researchers across the Globe to enhance the existing models shared through different platforms. In addition to that, many have come across having humanoids/robots deployed into streets for serving and public announcements, delivering medications or emergency support onto doorsteps. These technologies are also helping many organizations across planet to explore COVID-19 related useful solutions which can help to manipulate and process data in real time. In this paper, authors are concentrating on integrating the algorithmic approach of Edge Computing & Drone Technology which can enlighten the challenges of parameters namely latency, connectivity, data processing, onsite computation. etc. In addition to that, proposing an architecture for the design of Edge-based integrated Drone use case for the containment zones detection with offline data processing & computation and deployment of algorithm for thermal sensing. This approach of making UAV bandwidth-independent architecture will create new opportunities for exploring COVID Pandemic smoothness for every aspect of social duties. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.