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1.
3rd International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022 ; : 362-368, 2022.
Article in English | Scopus | ID: covidwho-2136266

ABSTRACT

Educational institutes across India have closed due to COVID-19 pandemic which has jeopardized academic schedules. To maintain their academic activities, several Indian educational institutes have shifted to online learning platforms. However, there are still questions about the effectiveness, design, and readiness of e-learning. In light of this fact, E-learning still tends to be controversial. As a result, it is inevitable to design an application with greater usability. In this paper, a novel application tool is developed and the design is proposed to enhance student knowledge and facilitate their study process, so they can study in comfort at home. The proposed system allows students to receive personalized educational assistance and also allows the students to get instant responses to all their questions throughout the day via a voice-enabled chatbot. It facilitates the connection between students and tutors, as well as the awarding of mind coins and badges based on how well they do, motivating them to learn more. Data analytics is incorporated and usability is measured. The result shows that the proposed system has greater usability resulting in a progressive improvement in the student's performance. © 2022 IEEE.

2.
Next Generation of Internet of Things ; 445:177-193, 2023.
Article in English | Web of Science | ID: covidwho-2085299

ABSTRACT

COVID-19 virus named CORONA is a vigorous disease spread all over the world very quickly and creates a pandemic situation to the human beings normal life. As per the doctors and researchers from the laboratory point of view, it will spread to a huge volume when humans are not followed certain principles. Moreover, this disease is easily transferred to neighbors and others in a short period which leads to death. To rectify the remedy for this virus, various spread countries and research peoples are creating the vaccines and some precautionary methods for living hood situation. Recent techniques are used to detect and monitoring the COVID-19- affected person's lifestyle and insisting they take precaution steps for early pre-pandemic life. IoT is a framework that is used to generate data from the human body from the sensors opted for human conditions. Wearable devices have been created with these sensors and communicated with human bodies directly or indirectly. The generated data will send through the server using any connectivity techniques such as Bluetooth or Wi-Fi. Analytics will be done at the server side for taking actions like the human body is affected by the COVID-19 virus or not. Finally, the generated data from a human can continuously store in real time in a cloud server which will be managed as a framework efficiently. This research work proposes a framework for data management in the early detection and monitoring of COVID-19 persons through IoT wearable devices in a pre-pandemic life. The experiments have been done at different zones, and the results are shown symptoms of COVID-19 disease. Parallel work reveals the data management in a cloud server since data have generated continuously in real time and tracking details also stored genuinely. Data management is the typical process in this research because all the data were generated in real time and analytics will be done whenever required. For that large amount of space and effective retrieval technique is required for data extraction. This research work data set is derived from various Internet sources like government web sites and mobile applications, and then, results have displayed the COVID-19 disease details accurately in real time.

3.
Social Behavior Research & Health ; 5(2):760-772, 2021.
Article in English | GIM | ID: covidwho-1635554

ABSTRACT

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (COVID-19) has affected over 250 million people globally and resulted in over 5 million deaths since it was first reported in November 2019.

4.
Capjournal ; - (30):28-32, 2021.
Article in English | Web of Science | ID: covidwho-1567468

ABSTRACT

Astronomers for Planet Earth (A4E) is a global collective, whose main goal is to communicate the fragility of our planet from an astronomical perspective. A4E works hard to equally engage with astronomers and educators worldwide, by encouraging the communities to reduce emissions and providing a space to collaborate and share resources. These actions have led to increased sustainability and the incorporation of climate change lessons and activities into teaching and outreach. With the global shift to online communication due to Covid-19, Astronomers for Planet Earth has utilised digital tools in the form of online conferences and seminars, high-impact journal articles, webinars, social media, and video production to engage its audience and grow a membership of around 1300 astronomers in 70 countries around the world. Our article addresses the importance of communicating the climate crisis from an astronomical perspective and explores the successes and challenges of our group's virtual communication with the astronomy community and the general public thus far.

5.
2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021 ; : 1364-1371, 2021.
Article in English | Scopus | ID: covidwho-1470296

ABSTRACT

Corona Disease Virus (COVID-19) is a rapidly spreading contagious viral disease that causes respiratory contaminations and is currently generating a worldwide medical crisis. It has caused a massive influence on people's lives, general well-being, and the global economy. Henceforth, it is critical to straightaway analyze the positive cases in order to keep the illness from spreading further and to regard infected patients as fast as could really be expected. Both patients and specialists will be benefitted by the early recognizable capability of outrageous COVID-19 by utilizing chest CT to examine biomedical images. RT-PCR (switch record polymerase chain response) based tests help to identify COVID-19, which has numerous limits. In this work, different CNN based Classifier model methodologies are utilized to follow the presence of COVID-19 from chest CT filter images of patients. In true indicative situations, a profound CNN-based methodology could be amazingly valuable in accomplishing quick COVID-19 testing. By utilizing irregularity data obtained from sifted images, image expansion enhances the number of profitable models for creating the CNN model. The proposed model has a grouping exactness of 95% for CT examines utilizing this strategy. With picture expansion, CT check pictures have an affectability of 94.78%and a particularity of 95.98%. The trial results were contrasted with ResNet-18, ResNet-50, and VGG-16 models, with freely available datasets containing CT images. © 2021 IEEE.

6.
Journal of Mobile Multimedia ; 18(1):135-162, 2022.
Article in English | Scopus | ID: covidwho-1404117

ABSTRACT

Vasovagal syncope (VVS) refers to fainting of people with a drop in blood flow to the brain more serious disease in paraplegia patients. Precognitive diagnoses are characterized by lightheadedness, nausea, severe fatigue, and an elevated heart rate. As a result, it’s important to seek care as soon as possible after experiencing syncope. Since receiving a correct diagnosis and appropriate care, the majority of patients may avoid complications with syncope. Syncope appears to be a sign of COVID 19 in people with coronary artery disease. Furthermore, a sudden heart attack might result in acute syncope. In a few circumstances, machine learning classification techniques may not be precise. For paraplegia patients, prediction vasovagal syncope needs more precise results in order to save their lives. The aim of this paper is to use the ensemble technique to improve the accuracy of conventional machine learning algorithms. EEG (ElectroEncephaloGram) brainwave dataset from kaggle is used to implement it. The accuracy of the proposed AWET algorithm is 82%. It improves the accuracy by 17% compare to Support Vector Machine, Random Forest, Naive Bayes, and MultiLayer Perceptron classifiers. © 2021 River Publishers

7.
J Intern Med ; 289(5): 726-737, 2021 05.
Article in English | MEDLINE | ID: covidwho-991594

ABSTRACT

BACKGROUND: Whilst the COVID-19 diagnostic test has a high false-negative rate, not everyone initially negative is re-tested. Michigan Medicine, a primary regional centre, provided an ideal setting for studying testing patterns during the first wave of the pandemic. OBJECTIVES: To identify the characteristics of patients who underwent repeated testing for COVID-19 and determine if repeated testing was associated with downstream outcomes amongst positive cases. METHODS: Characteristics, test results, and health outcomes for patients presenting for a COVID-19 diagnostic test were collected. We examined whether patient characteristics differed with repeated testing and estimated a false-negative rate for the test. We then studied repeated testing patterns in patients with severe COVID-19-related outcomes. RESULTS: Patient age, sex, body mass index, neighbourhood poverty levels, pre-existing type 2 diabetes, circulatory, kidney, and liver diseases, and cough, fever/chills, and pain symptoms 14 days prior to a first test were associated with repeated testing. Amongst patients with a positive result, age (OR: 1.17; 95% CI: (1.05, 1.34)) and pre-existing kidney diseases (OR: 2.26; 95% CI: (1.41, 3.68)) remained significant. Hospitalization (OR: 7.88; 95% CI: (5.15, 12.26)) and ICU-level care (OR: 6.93; 95% CI: (4.44, 10.92)) were associated with repeated testing. The estimated false-negative rate was 23.8% (95% CI: (19.5%, 28.5%)). CONCLUSIONS: Whilst most patients were tested once and received a negative result, a meaningful subset underwent multiple rounds of testing. These results shed light on testing patterns and have important implications for understanding the variation of repeated testing results within and between patients.


Subject(s)
COVID-19 Nucleic Acid Testing , COVID-19 , False Negative Reactions , Intensive Care Units/statistics & numerical data , SARS-CoV-2/isolation & purification , Age Factors , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19/physiopathology , COVID-19/therapy , COVID-19 Nucleic Acid Testing/methods , COVID-19 Nucleic Acid Testing/standards , COVID-19 Nucleic Acid Testing/statistics & numerical data , Comorbidity , Diagnostic Errors/prevention & control , Female , Hospitalization/statistics & numerical data , Humans , Kidney Diseases/epidemiology , Male , Michigan/epidemiology , Middle Aged , Public Reporting of Healthcare Data , Severity of Illness Index , Socioeconomic Factors
8.
J Hosp Infect ; 111: 102-106, 2021 May.
Article in English | MEDLINE | ID: covidwho-968986

ABSTRACT

BACKGROUND: Healthcare workers have been at increased risk of exposure, infection and serious complications from COVID-19. Antibody testing has been used to identify staff members who have been previously infected by SARS-CoV-2, and has been rolled out rapidly in the United Kingdom. A number of comment and editorial articles have been published that raise concerns about antibody testing in this context. We present perceptions of National Health Service (NHS) healthcare workers in relation to SARS-CoV-2 antibody testing. METHODS: An electronic survey regarding perceptions towards SARS-CoV-2 antibody testing was distributed to all healthcare workers at a major NHS tertiary hospital following implementation of antibody testing. RESULTS: In total, 560 healthcare workers completed the survey (80% female; 25% of Black and Minority Ethnic background; 58% from frontline clinical staff). Exploring whether they previously had COVID-19 was the primary reported reason for choosing to undergo antibody testing (85.2%). In case of a positive antibody test, 72% reported that they would feel relieved, whilst 48% felt that they would be happier to work in a patient-facing area. Moreover, 12% responded that a positive test would mean "social distancing is less important", with 34% of the responders indicating that in this case they would be both less likely to catch COVID-19 and happier to visit friends/relatives. CONCLUSIONS: NHS staff members primarily seek out SARS-CoV-2 antibody testing for an appropriate reason. Based on our findings and given the lack of definite data regarding the extent of immunity protection from a positive SARS-CoV-2 antibody test, significant concerns may be raised regarding the reported interpretation by healthcare workers of positive antibody test results. This needs to be further explored and addressed to protect NHS staff and patients.


Subject(s)
Antibodies, Viral/blood , Attitude of Health Personnel , COVID-19 Testing/statistics & numerical data , COVID-19/prevention & control , Health Personnel/psychology , Health Personnel/statistics & numerical data , Occupational Diseases/prevention & control , Adolescent , Adult , Aged , Female , Humans , Male , Middle Aged , Occupational Diseases/blood , SARS-CoV-2 , United Kingdom , Young Adult
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