Novel Framework to Define Extended & Mixed Reality for Online Learning

COVID-19 has taken educational protocols to different track. Online education is the way to execute process smoothly. There are various tools that are providing services to fill the pain points. Role of emerging technologies can't be denied. Extended and mixed reality plays a vital role here. Our purpose is to analyze the same in this paper. Second objective of this paper is to develop novel framework to define extended and mixed reality for online learning Fig.∼\ref{fig1}. Testing has been done on four Indian universities and schools to identify the effectiveness of proposed framework. © 2022 IEEE.

Analysis of Emerging Preprocessing Techniques Combined with Deep CNN for Lung Disease Detection

Data preprocessing is one of the pertinent steps while classifying images via CNN models. The efficiency of any model depends on the quality of the dataset it deals with. A clean dataset provides an efficient platform for a model to tackle classification and segmentation issues. Our paper focuses on three emerging data preprocessing techniques: Real ESRGAN, Swin IR, and GFPGAN over the lung disease dataset. We have used three models: Mobile net, Densenet201, and NasNet, to carry out classification tasks on Chest X-Ray images of six different types of lung disease: Bacterial Pneumonia, Viral pneumonia, Lung opacity, Covid, Tuberculosis, and Normal. Analysis of the aforementioned preprocessing techniques followed by classification via three CNN models (Mobile net, Densenet, and NasNet) are carried out on lung disease dataset, and their accuracy prediction, Training, and validation loss are extensively compared. © 2022 IEEE.

Online Teaching during Covid-19 Pandemic-Perceptions of Undergraduate Medical Students in Uttar Pradesh, India

Background: The suspension of regular face to face teaching during Covid Pandemic lead to emergence of e learning with full swing in every field of education including Medical Colleges. Students perceived this unplanned shift differently. So, this study was planned to explore the perceptions of medical students in a private medical university, UP, India. Method(s): A questionnaire was designed on google form with close ended questions & likert scale questions. Link was shared with medical students who have attended online classes during Covid pandemic. Respondents were 140 medical undergraduates from 1st Professional, regular & supple batch. Responses were analyzed & results obtained Results: Majority of students (76%) used smart phones to attend online classes & Google meet was the preferred platform (45.35%). Duration of online classes preferred by students was 30-45min (54.28%). Usefulness of online teaching by most of the students perceived as passable (Likert scale, LS-2.84). Extent of understanding the topic was not equivalent to face to face (LS-2.9) & internet connectivity posed problems (LS-3.77) that is why most of the students demanded for reconduction of classes after resumption of regular offline classes (LS-3.91) Most of them agreed that medical learning is suffering as practical classes cannot be conducted online (LS-3.98). Most of the students (45%) confessed that self-study was less at homes as compared to their hostels. Both students & their parents were worried about quality of studies & their future performance in exams (LS 4.02 &3.66). Students were not in favour of online teaching in future (LS-2.31) Conclusion(s): Online teaching was well received by medical students but they faced several challenges like sometimes internet connectivity issues, less student teacher interaction, methodology barriers, less development of practical skills. Despite all the hassles, chain of learning did not break due to online teaching. Efforts should be done to address the problems faced by students at individual faculty level as well as Institute level. Copyright © 2022, Dr Yashwant Research Labs Pvt Ltd. All rights reserved.

Application of Voting Based Approach on Deep Learning Algorithm for Lung Disease Classification

With the advent of the Deep learning era, an unprecedented change has come in the field of medical image analysis via CAD (Computer-Aided Diagnosis) [1]-[13] system. With feature extraction capability, Deep learning effectively performs the classification task and thus enhances the prediction of Medical images. CNN models like Dense net 121, Resnet-50, Alex net, Mobile Net, and Inceptionv3 have been used to identify lung disease, but no model was able to predict the particular class of illness with 100% accuracy. In this paper, we apply the voting method, which combines three models Dense net 121, Mobile Net, NasNet, and predictions are made on the basis of the majority of optimistic predictions. Our approach was found to improve the prediction of a particular class of lung disease like Bacterial Pneumonia, Covid, and Lung Opacity. Normal lungs are predicted with 100% accuracy with our approach. © 2022 IEEE.

COVID-19 Real Time Impact Analysis India vs USA

This is the time when the whole world is facing a crisis like never before, which has taken the form of a pandemic called the Coronavirus outbreak. The situation is way bigger and tense than it seems. The outbreak of COVID-19 has exposed both the developed and developing nations of the world with an evolving challenge like never before. All the developed nations are witnessing unprecedented collapse of their public healthcare systems and institutions, weak enforcement of laws to prevent the spread of infection and unimpressive crowd management techniques. We can hear health officials calling for huge drastic & rapid responses in early days when the infected number of people were relatively small. Some people are telling that we are overreacting but that is not true. It was never really fine to begin in such a fashion but if we don’t notice the seriousness of this crisis it will be very late. The following research is based on insights & comparisons between India and United States and the reason for choosing the strong & powerful nations are as follows: India is still counted as a developing nation whereas, USA is the most developed country in the world.The healthcare facilities in USA are way advance as compared to India yet the number of cases there were extremely high.India and USA also have a huge difference when it comes to the population and yet the number of cases each day is quite low in India. The number of recovery cases are also higher in India. So, the question is What went wrong? Why is India in a better place in comparison to the world’s super power USA in this pandemic? © 2021, Springer Nature Singapore Pte Ltd.