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1.
Journal of Advances in Information Technology ; 13(6):597-603, 2022.
Article in English | Scopus | ID: covidwho-2145293

ABSTRACT

—The current COVID-19 pandemic has elevated the importance of cleanliness and social distancing. These needs will continue to be important as the world moves to a new normal whilst navigating through a post-covid environment. This paper presents a use case application that focuses on enforcing safe distance measures inside a campus building where there is limited manpower resources. Amidst the social setting within the university, staff or students may at times accidentally congregate, which may lead to spread of diseases inconveniencing all affected parties. Our proposed integrated solution consists of a network of video cameras and sensors which allows one to monitor behavior within the building. The integrated smart devices communicate with (1) an analytics server that processes the data from the various sensors and (2) a platform that integrates the analytic results and optimizes the action items to be reflected to the environment. A pilot prototype has been deployed and evaluated within a living lab setting on campus. Results show that the system is useful in streamlining the operational process resulting in more efficient processes and procedures to help enforce safe management measures needed to maintain proper social distancing among occupants in campus. © 2022 by the authors.

2.
5th International Conference on Innovative Computing and Communication, ICICC 2022 ; 471:205-214, 2023.
Article in English | Scopus | ID: covidwho-2094499

ABSTRACT

In the era of demonetization, the banking sector has seen an exponential increase in the usage of digital payments. There has been a slew of digital payment networks proposed by both corporate and public entities. These platforms are being used by users to make payments, pay bills, and send money. The cost of Internet plans, the availability of low-cost mobile handsets, and technological savvy are just a few of the factors driving this digital revolution. Although private companies’ platforms are preferred by the bulk of people using digital platforms, public players are continually bringing novel ideas to the table, such as UPI. Another new payment platform named e-Rupi has been created and released for users by the Indian government in a similar endeavor. This platform attempts to use a voucher-based system to deliver social programs, health benefits, and a variety of other services. Hence, this paper investigates the detailed functionality of the e-Rupi platform and performs an empirical evaluation and comparative analysis of e-Rupi with other digital payment platforms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

3.
International Conference on Advances and Applications of Artificial Intelligence and Machine Learning, ICAAAIML 2021 ; 925:427-438, 2022.
Article in English | Scopus | ID: covidwho-2075303

ABSTRACT

Since the approach of the internet, many fake news and fabricated articles/contents observed widely. With the growing utilization of advancement and social media, buyers are making and sharing more information than some other time in recent memory. However, some individuals distributed counterfeit news with no significance to reality just to build the readership. Gossip distinguishing on social media is an essential issue. This paper talks about the methodology of machine learning and natural language processing to solve this problem. Use of TF-IDF (TermFrequencyInverse Document Frequency) and trained the data on four classifiers to explore which amongst them works well for this Indian dataset (https://github.com/Aks121/Fake-News-Analysis-on-Indian-Dataset ).The recall, precision and F1 scores help us figure out which model works best. The accuracy achieved so far is 95 on the ratio of 70:30 split dataset. The reason for this work is to approach the mechanized arrangement of the news stories utilizing machine learning. This can be used by the users to identify through the locales containing fake news. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

4.
JMS - Journal of Medical Society ; 36(1):11-17, 2022.
Article in English | Scopus | ID: covidwho-2030165

ABSTRACT

Background: With the emergence of highly infectious epidemics/pandemics, such as Ebola virus diseases, severe acute respiratory syndrome, and coronavirus disease-2019 (COVID-19), doctors are at much greater risk of infection due to the exposure to the highly infectious bodily fluids and droplet nuclei. Hence, treating and caring for patients need the use of personal protective equipment (PPE) to reduce the transmission risk. Objectives: The present study was conducted to estimate the prevalence of skin injury and its type due to PPE usage, to find the association of related factors with the skin injuries among doctors. Materials and Methods: This descriptive cross-sectional study was conducted after obtaining the institutional ethical approval in dedicated COVID-19 hospital for a period of 4 months among 132 doctors wearing grades 2 and 3 PPE kit using a questionnaire collecting the details regarding baseline, duty, skin injury characterization. During analysis of data, an association between variables was significant for P < 0.05. Results: It was observed that 17.1% of doctors were wearing the PPE kit for 5 or more hours/and 13.0% of subjects reported absenteeism from duty hours due to PPE-induced skin injuries. 76.4% of subjects have suffered from skin injury after PPE usage. The most common symptoms/signs for the skin injury occurred was indentation and pain on back of ears (61.0%). Conclusion: The skin injuries of PPE among the doctors may result in reduced morale for overloaded work and made them anxious. Hence, an appropriate monitoring of these adverse effects should be done and effective preventive measures should be adopted. © 2022 Journal of Medical Society ;Published by Wolters Kluwer - Medknow.

5.
Indian Journal of Critical Care Medicine ; 26:S116, 2022.
Article in English | EMBASE | ID: covidwho-2006404

ABSTRACT

Background: Hospitalised COVID-19 patients are known to exhibit varying degrees of immune dysfunction, few modifiable risk factors have been identified to improve this state of which one is the immune modulator effects of vitamin D. Vitamin D is being prescribed as a treatment of COVID-19 in a few guidelines as there is generalised assumption that vitamin D enhances immunity during this illness. So this is an attempt to find out whether a deficiency of vitamin D is associated with the severity of COVID-19. Aim: To study the relationship of serum 25 hydroxy vitamin D [25(OH)D] deficiency with disease severity in hospitalised COVID-19 patients. Materials and methods: The present case-control study compared serum 25(OH)D levels among Mild to moderate and severe COVID- 19 patients. Around 39 diagnosed and Hospitalised Severe COVID- 19 disease are compared with 39 Hospitalised Mild and Moderate COVID-19 disease in Care Hospital, Bhubaneswar, Odisha, India between April 1, 2021, ad August 31, 2021. Patients were divided into 2 groups. The Group 1-Mild to Moderate infection with CT Severity index < 10/25 and Group 2-Severe Infection with HRCT Chest of CTSI >10/25. As per hospital policy, severe infection patients were kept in Critical Care Area and Mild infection patients were kept in Ward/Cabin areas. Any patients becoming sick and being transferred to critical areas are shifted from Group 1 to Group 2 after HRCT chest. Vitamin D levels (25 D Cholecalciferol) are done on the day of admission by chemiluminescence immunoassay test after taking due consent from the patients/attenders. The level of cut-off used in our study is 20 ng/mL. The association was analysed using regression analysis and other statistical methods. Results: The status of 25(OH)D deficiency (present/absent with cut-off being 20 ng/mL) showed no significant difference among cases and control at p < 0.05. Chi-square statistics with Yates correction is 1.8909. The p value is 0.169099. So there were no significant differences in vitamin D3 levels between Mild to moderate and Severe COVID- 19 patients. Conclusion: 25(OH)D levels appear to have no strong association with disease severity amongst hospitalised COVID-19 patients. Hence, its prescription for COVID-19 treatment as well as prevention needs to be reconsidered.

6.
2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022 ; : 1003-1006, 2022.
Article in English | Scopus | ID: covidwho-1992620

ABSTRACT

This is a paper on disease prediction using machine learning through a python graphical user interface application. The motivation behind this application is the pandemic (Covid- Situation) faced by the whole world and also the idea to robotize the current manual framework of initial diagnosis by the assistance of mechanized supplies and undeniable PC programming so that their important information/data can be put away for a more drawn out period and also for a more useful purpose. This paper introduces the field of diseases prediction, the treatment for the disease, and consulting with the doctors nearby through efficient programming using machine learning. It describes the need for a system of an online artificial doctor, which will not only help them in predicting and understanding the diseases, but it will also advise them of certain medicines that are necessary for controlling or curing those diseases. © 2022 IEEE.

7.
3rd International Conference on Machine Intelligence and Signal Processing, MISP 2021 ; 858:19-33, 2022.
Article in English | Scopus | ID: covidwho-1958922

ABSTRACT

The COVID-19 pandemic has caused economic, physiological, and psychological harm to the world. A crucial step, hence, in the fight against covid is the highly efficient screening of patient cases. Conventional RT-PCR testing, even though more reliable, cannot be done on every patient as the virus has spread way faster than the world’s resources could afford. One very important screening approach that is being used across the globe is chest X-ray imaging. Since X-ray facilities are readily obtainable in healthcare systems of most countries across the globe, and with more and more X-ray systems being digitized, the cost and time of transportation are cut as well. Hence, if the detection of the virus in a CXR image can be automated using AI techniques, it will save a lot of time and effort of radiologists to have to go through hundreds of such images, and in some cases will also spare the need of doing RT-PCR testing, and since saving resources in this time is vital, automated detection can be very effective. In this work, we will explore, analytically discuss, and do a comparative study of many ML and deep learning techniques that have been taken for automated COVID-19 detection through chest X-rays (CXR). We carefully analyze the papers and derive a set of key factors for discriminating the methodologies, classification techniques, approaches, and the results that yielded. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

8.
1st International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2022 ; : 1-6, 2022.
Article in English | Scopus | ID: covidwho-1932073

ABSTRACT

COVID-19 has taught us the need of practicing social distancing. In the year 2020 because of sudden lockdown across the globe, E-commerce websites and e-shoppingwere the only escape to fulfill our basic needs and with the advancement of technology putting your websites online has become a necessity. Be it food, groceries, or our favorite outfit, all these things are now available online. It was noticed during the lockdown period that the businesses that had no social presence suffered heavy losses. On the other hand, people who had established their presence on the internet saw a sudden boom in their overall sales. This project discusses how the recent advancement in the field of Machine Learning and Artificial Intelligence has led to an increase in the sales of various businesses. The machine learning model analyses the pattern of customer's behavior which affects the sales builds a dataset after many observations and finally helps generate an algorithm which is an efficient recommendation system. This project also discusses how cyber security helps us have secured and authenticated transactions which have aided e-commerce business growth by building customer's trust. © 2022 IEEE.

9.
European Stroke Journal ; 7(1 SUPPL):355, 2022.
Article in English | EMBASE | ID: covidwho-1928135

ABSTRACT

Background: During the second wave of COVID-19, India suffered from a catastrophic outburst of cases and rapid transmission of disease due to the highly infectious delta strain (B.1.617.2). Patients infected with this strain underwent prolonged hospitalisations, suffered from severe symptoms. A sudden surge of fungal infections, primarily Mucormycosis was observed. Methods: We conducted a case-control study to study various risk factors and form of intracranial involvement in cases of Mucormycosis. Results: Study included 121 patients in total;out of which 61 were Mucormycosis patients with prior COVID-19 infection. 30 out of 61 Mucormycosis patients had intracranial involvement with majority having stroke in the form of the either infarct (10 patients, 34%);or haemorrhage (3 patients, 10%) and thrombosis of artery involvement (8 patients, 29%). Other intracranial form of involvement was abscess (6 patients, 20%) and meningitis (2 patients, 7%). The most frequent type of infarcts were lacunar infarcts and the most common location of infarcts were middle cerebral artery (MCA) or anterior cerebral artery (ACA). Patients were treated with administration of Amphotericin B and Posaconazole. Telephonic follow-up was conducted after a time period of about 90 days and their health condition was recorded on basis of modified ranking scale (mRS). Out of the 30 Mucormycosis infection patients displaying the occurrence of stroke, 10 patients could not survive. q Conclusion: Intracranial Mucormycosis in COVID19 patients presenting with stroke were observed frequently and had mortality in about one-third cases.

10.
17th International Conference on Web Information Systems and Technologies (WEBIST) ; : 275-282, 2021.
Article in English | English Web of Science | ID: covidwho-1884609

ABSTRACT

Following the outbreak of the Coronavirus (COVID-19) pandemic, many organisations have shifted to remote working overnight. The new reality has created conditions to use smart home technologies for work purposes, for which they were not originally intended. The lack of insights into the new application of smart home technologies has led to two research objectives. First, the paper aimed to investigate the factors correlating with productivity and perceived wellbeing. Second, the study tried to explore individuals' intentions to use smart home offices for remote work in the future. 528 responses were gathered from individuals who had smart homes and had worked from home during the pandemic. The results showed that productivity positively relates to service relevance, perceived usefulness, perceived ease of use, hedonic beliefs, control over environmental conditions, innovativeness and attitude. Task-technology fit, service relevance, attitude to smart homes, innovativeness, hedonic beliefs, perceived usefulness, perceived ease of use and control over environmental conditions correlate with perceived wellbeing. The intention to work from smart home-offices in the future is determined by perceived wellbeing. Findings contribute to the research on smart homes and remote work practices, by providing the first empirical evidence about the new applications and outcomes of smart home use in the work context.

11.
Frontiers in Sustainable Cities ; 4, 2022.
Article in English | Scopus | ID: covidwho-1875444

ABSTRACT

The smart city term has been widely used for a number of years and many pilot projects and limited scale, sector independent initiatives have been progressed, but comprehensive, long-term, city wide, multi-sector systems are much less evident. This paper examines one such case study in Newcastle, UK highlighting the challenges and opportunities that realizing “smart city” concepts at scale present. The paper provides the background to the Newcastle Urban Observatory project and discusses the socio-technical and practical challenges of developing and maintaining smart city networks of sensors in the plurality that is a modern city. We discuss the organizational requirements, governance, data quality and volume issues, big data management and discuss the current and future needs of decision makers and other city stakeholders. Finally, we propose areas where smart cities can have a positive impact on public outcomes through the discussion of two case studies related to COVID-19 and pedestrianization initiatives. Copyright © 2022 James, Jonczyk, Smith, Harris, Komar, Bell and Ranjan.

12.
2022 International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2022 ; : 8-14, 2022.
Article in English | Scopus | ID: covidwho-1874306

ABSTRACT

The concept of e-learning is not new to the education sector. However, in the recent years, with the outbreak of COVID-19, the importance of e-learning has grown globally. It has completely transformed the way in which learning is imparted to students. Unlike traditional chalk and board method of teaching, e-learning makes learning simpler, easier, and more effective. Earlier the access to knowledge was not accessible to all. Students with economic constraints, geographical boundaries or physical disabilities had scarce opportunities in the academic province. The concept of online education has broken all these barriers. Today's learners are engaged in appropriate, mobile, self-paced, and customized content. This need is satisfied by the online style of learning, where students can study at their own convenience and demand. This research work has proposed an E-Learning Website for Beginners especially designed keeping in mind the students of rural areas and backward classes who may not have access to correct and sufficient resources to learn the tools which are required in day-to-day life. The web-application will provide the user a complete basic knowledge on the various Microsoft Office Tools through videos, images and text materials provided on the platform. There is a quiz at the end of every course, so that students can examine themselves. Students can also download the course material from the platform. Being an open-source platform, this e-learning website can be used by any school or college students. © 2022 IEEE.

13.
Asian Journal of Chemistry ; 34(5):1105-1112, 2022.
Article in English | Scopus | ID: covidwho-1835973

ABSTRACT

With the emergence of COVID-19 in late December 2019 in China and its exponential spread around the globe, on 11th March 2020 WHO declared it global pandemic. The first case of novel coronavirus in India was reported on 30th January 2020 in Kerala state of India. India is currently experiencing the worst situation amid COVID-19 pandemic with its 3rd position having the highest number of confirmed cases amongst the countries around the world with huge social and economic losses. Many studies reported that there is an improvement in air quality around different parts of the world due to cessation of vehicular, industrial and anthropogenic activities. The present study highlights the impact of COVID-19 pandemic on air quality over India during the lockdown period amid COVID-19 pandemic. Results revealed the significant decline in NO2 and aerosol optical depth (AOD) all around in India except for ozone. There has been a considerable decline in air pollution because of restricted activities during COVID-19 pandemic over India. Meteorological factors may not be directly related to the number of outbreaks. Although the COVID-19 lockdown has a negative impact on economic aspects but it has a positive impact on air quality. The COVID-19 pandemic impacted the lives of millions and having numerous global implications made humans believe that nothing will be normal as earlier. The study may help authorities and policy makers on taking specific measures for the pandemic it can be helpful in future to frame policies to reduce air pollution by policy makers. © 2022 Chemical Publishing Co.. All rights reserved.

14.
2021 International Conference on Computational Performance Evaluation, ComPE 2021 ; : 832-835, 2021.
Article in English | Scopus | ID: covidwho-1831752

ABSTRACT

Due to the effect of Covid-19 the pattern of energy consumption of Uttarakhand State has affected during lockdown. Since the inception of Covid-19 in Uttarakhand there has drastic change in electricity consumption in thirteen districts of the State including Dehradun which is also a Smart City. It has reported that there is decrease in electricity consumption in the year 2020-21. In this study the long-term load forecasting using Artificial Neural Network is used as per the information released by Uttarakhand Electricity Regulatory Commission (UERC) in their tariff order for Financial Year 2021-22. There is eleven million population in Uttarakhand at present. During economic shutdown in Uttarakhand State the power utilities has faced the challenge of electricity generation, transmission, and distribution. It has been observed that during Covid-19 there is 939.97 million units generated energy loss has faced by power utilities companies in Uttarakhand. Uttarakhand is a emerging State where lots of new Technologies are in pipeline. In this Study the forecasted results is for nine years (2022-2030) which represents that there will be sudden rise in electricity consumption after 2025 to 2030 in Uttarakhand due to the intervention of electric vehicles. In Uttarakhand Dehradun is also a smart city where lots of IoT devices have been deployed across city which are are also consuming electricity. This study has reduced the forecast error upto 7.17 % so that there would be minimum revenue loss in future to the power utilities in Uttarakhand. © 2021 IEEE.

15.
European Urology ; 79:S1388, 2021.
Article in English | EMBASE | ID: covidwho-1747409

ABSTRACT

Introduction & Objectives: The current coronavirus disease 2019 (COVID-19) pandemic is creating huge pressure on our health care systems and has led to dramatic changes in our daily lives. Many countries have enforced strict controls on movement and socializing in an effort to manage the pandemic. Both, in-patient and out-patient care has been affected. There is big gap between health care service providers and patients and because of that many people are suffering. But telemedicine appears to be only bridge between them so that patients can get maximum benefit from the experts. This study is being conducted to know the worth of telemedicine in urology during ongoing COVID pandemic and for future prospect. Materials & Methods: All the patients who made a call on telemedicine contact number of department of urology of our tertiary care hospital and took advice for their treatment or follow up from April 2020 to December 2020, were included in this prospective observational study. Patients contacted us through various modalities like Voice/video call, WhatsApp chat, messages. Patients who contacted us for non-urological problem were excluded. All calls were answered by Professional Urologist and advice was given verbally as well as sent them in written on a prescription slip through WhatsApp. Data collection included age, sex, place, symptoms and advice given. Results: During the study period, we received 1102 calls from the patients of North India, 124 patients were excluded for being non-urological and 978 patients were included. 94% patients contacted us through voice call, 4% through video call and 2% through chat only. Average duration of call was 16 minutes and 25 seconds. 68% patients were males, while 32% females. 54% patients were younger than 40 years and only 15% were elder than 60 years. Common reasons for calling us were- urinary tract infection (23%), lower urinary tracts symptoms (21%), renal stone disease (17%), haematuria (11%), post-operated cases (11%) and sexual problems (7%). Approximately 16% patients had some urological malignancy. Only 18% patients contacted us for acute illness of duration <1 week, while 47% patients were sick for >4 weeks. 18% patients needed only counselling for their disease, 65% required prescription and conservative management. 17% patients were requiring in-hospital management so referred to nearby urological center for urgent intervention or care. None of the patients had any problem in getting medications from pharmacy. Conclusions: Telemedicine provides specialized clinical support for urologists and patients just by using mobile phones, as a logistically feasible alternative to face-to-face consultation. 83% of cases were successfully managed just by telemedicine and very useful for reducing the risk of transmission of COVID-19 infection. This novel way of urological practice should be continued in future to reduce unnecessary visits to medical facilities even after this pandemic.

16.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; : 8558-8562, 2021.
Article in English | Web of Science | ID: covidwho-1532685

ABSTRACT

To mitigate the outbreak of highly contagious COVID-19, we need a sensitive, robust automated diagnostic tool. This paper proposes a three-level approach to separate the cases of COVID-19, pneumonia from normal patients using chest CT scans. At the first level, we fine tune a multi-scale ResNet50 model for feature extraction from all the slices of CT scan for each patient. By using multi-scale residual network, we can learn different sizes of infection, thereby making the detection possible at early stages too. These extracted features are used to train a patient-level classifier, at the second level. Four different classifiers are trained at this stage. Finally, predictions of patient level classifiers are combined by training an ensemble classifier. We test the proposed method on three sets of data released by ICASSP, COVID-19 Signal Processing Grand Challenge (SPGC). The proposed method has been successful in classifying the three classes with a validation accuracy of 94.9% and testing accuracy of 88.89%.

17.
International Journal of Emerging Technologies in Learning ; 16(16):169-185, 2021.
Article in English | Scopus | ID: covidwho-1395065

ABSTRACT

This quantitative study proposes and validates the Hybrid force model by analysing the challenges and opportunities in online education during COVID-19 through an online survey from students and teachers of Indian higher education institutions. The proposed model considers the learner as a system of study and talks about the amalgamation of knowledge, human force (teacher) and technological force for better online learning opportunities and experience. The results show Google Meet, Zoom and Microsoft Team as the main online platforms for imparting the classes while almost 80% of the students prefer a non-traditional teaching method (online and hybrid). The results highlight that more than 88% of the students prefer to have a personal teaching assistant in their learning trajectory. © 2021, International Journal of Emerging Technologies in Learning. All Rights Reserved.

18.
5th International Conference on Trends in Electronics and Informatics, ICOEI 2021 ; : 1231-1237, 2021.
Article in English | Scopus | ID: covidwho-1393733

ABSTRACT

The COVID-19 coronavirus pandemic is wreaking havoc on the world's health. The healthcare sector is in a state of disaster. Many precautionary steps have been taken to prevent the spread of this disease, including the usage of a mask, which is strongly recommended by the World Health Organization (WHO). In this paper, we used three deep learning methods for face mask detection, including Max pooling, Average pooling, and MobileNetV2 architecture, and showed the methods detection accuracy. A dataset containing 1845 images from various sources and 120 co-author pictures taken with a webcam and a mobile phone camera is used to train a deep learning architecture. The Max pooling achieved 96.49% training accuracy and validation accuracy is 98.67%. Besides, the Average pooling achieved 95.190/0 training accuracy and validation accuracy is 96.23%. MobileNetV2 architecture gained the highest accuracy 99.72% for training and 99.82 % for validation. © 2021 IEEE.

19.
European Urology ; 79:S1388-S1388, 2021.
Article in English | Web of Science | ID: covidwho-1357932
20.
Journal of the Optical Society of America B: Optical Physics ; 38(5):1702-1709, 2021.
Article in English | Scopus | ID: covidwho-1227666

ABSTRACT

Angle-resolved circularly polarized light scattering calculations are demonstrated to identify virus particles from nonvirus particles. A coronavirus particle is modeled as having a spherical shaped envelope with cylindrical spikes projected from the envelope surface, and the single-stranded ribonucleic acid (RNA) genome polymer has been mimicked with a toroidal helix. The influence of genome polymer packaged as a standard helix in the virion core is also demonstrated. We investigated four different electromagnetic models: (i) a nucleated sphere with spikes that is a coronavirus particle, (ii) a nucleated sphere with no spikes, (iii) a homogeneous sphere, and (iv) a respiratory fluid containing a virus particle. The angular pattern of scattered circularly polarized light, the circular intensity differential scattering of light (CIDS), served as a particle's signature. This scattering signature is found sensitive to the chiral parameters that reveal information about the particles. The effect of changes in the RNA polymer, changes in its packaging, number of turns, handedness, and size are demonstrated on the scattering calculations. Additionally, the extinction efficiency, the depolarization ratio, the total scattered intensity, and the effect of changes in the wavelength of incident light on these scattering quantities are investigated. This biophysical method can offer a label-free identification of virus particles and can help understand their interaction with light. © 2021 Optical Society of America

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