COVID-19

This is a research about a method that I studied to treat virus COVID-19 or any other viruses by modifying and tricking the virus .

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The problem of effective disposal of the trash generated by people has rightfully attracted major interest from various sections of society in recent times. Recently, deep learning solutions have been proposed to design automated mechanisms to segregate waste. However, most datasets used for this purpose are not adequate. In this paper, we introduce a new dataset, TrashBox, containing 17,785 images across seven different classes, including medical and e-waste classes which are not included in any other existing dataset.

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<p>This multilingual Twitter dataset spans over 2 years from October 2019 to the end of 2021,&nbsp;including 3 months before the outbreak of the COVID-19&nbsp;pandemic.</p>

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We create a thermal infrared face dataset (TIF) for fever screening. TIF is collected at the entrance of our university’s engineering building. The infrared face images are captured by an infrared camera under different environmental conditions.

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This dataset includes (i) mental health and emotional wellbeing; (ii) factors / stressors in the work environment; (iii) organizational and social support; (iv) personal characteristics; and, (v) demographics.

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360 Views

Please cite the following paper when using this dataset:

N. Thakur and C.Y. Han, “An Exploratory Study of Tweets about the SARS-CoV-2 Omicron Variant: Insights from Sentiment Analysis, Language Interpretation, Source Tracking, Type Classification, and Embedded URL Detection,” Journal of COVID, 2022, Volume 5, Issue 3, pp. 1026-1049

Abstract

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 The respiratory includes selected files related to a  study of physiological changes recorded by wearable devices during physical exercise on a home exercise bike. It is focused on testing the effect of face masks and respirators on blood oxygen concentration, breathing frequency, and the heart rate changes.

 

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201 Views

Please cite the following paper when using this dataset:

N. Thakur, “A Large-Scale Dataset of Twitter Chatter about Online Learning during the Current COVID-19 Omicron Wave,” Journal of Data, vol. 7, no. 8, p. 109, Aug. 2022, doi: 10.3390/data7080109

Abstract

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509 Views

Please cite the following paper when using this dataset:

N. Thakur, “MonkeyPox2022Tweets: A large-scale Twitter dataset on the 2022 Monkeypox outbreak, findings from analysis of Tweets, and open research questions,” Infect. Dis. Rep., vol. 14, no. 6, pp. 855–883, 2022, DOI: https://doi.org/10.3390/idr14060087.

Abstract

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2888 Views

A shortage of beds and cross-infection in hospitals due to patient crowding and overloading during the COVID-19 pandemic necessitate the use of telemedicine over face-to-face treatment. This study used statistical analysis to evaluate the impact of treatment choice among hospitals, patients, and the government to encourage them to employ telemedicine to avoid overload risk in the IoT environment during the pandemic by analyzing data from Tongji Hospital of Wuhan, China from January to September 2020.

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420 Views

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