ABSTRACT
Social media is used by people to communicate with friends and to share information, such as their feelings and moods. This enables companies to better understand how people think, feel, and act when communicating on various online platforms by analysing emotional data from social networks. People don't seek expert assistance because they are unwilling to do so. Additionally, many people who were kept inside their houses due of the Covid 19 pandemic decided to vent themselves on social media. We intend to create and develop a Chrome plugin that will instantly evaluate the user's tweet in order to solve this issue. Our technology would assess their posts using a machine learning model, then query them. The system will decide whether a user needs professional help based on how they respond to the questions. © 2022 IEEE.
ABSTRACT
Introduction Radiological Society of the Netherlands introduced the coronavirus disease 2019 (COVID-19) Reporting and Data System (CO-RADS) and the corresponding CT severity score (CTSS) to diagnose COVID-19 severity. However, data regarding the same is very limited. Objectives The objective of this study was to correlate the computed tomography severity scoring (CTSS) on high-resolution computed tomography (HRCT) thorax and inflammatory markers with COVID-19 related mortality. Methods A retrospective observational study was conducted in a tertiary center between June 2020 to May 2021 among 2343 adult patients at the department of radio-diagnosis with suspected and confirmed COVID-19 cases who received an HRCT thorax. Data was collected retrospectively from the records regarding age, sex, and information regarding inflammatory markers such as C-reactive protein (CRP), ferritin, lactate dehydrogenase (LDH), erythrocyte sedimentation rate (ESR), D-dimer, and neutrophil-to-lymphocyte ratio. Information on HRCT thorax of patients was reviewed for radiological suspicion of COVID-19 related lung changes using CO-RADS scoring and severity of lung involvement using CT-severity scoring. Data was analyzed using SPSS version 22 (IBM Inc., Armonk, New York). Results The mean age was 51.69 ± 16.02 years, and most of the study participants were male (1592, 67.95%). The majority (999, 42.64%) had diabetes as a comorbidity. The reverse transcription polymerase chain reaction (RT-PCR) test was positive in 1571 (67.05%) participants. The majority (1571, 67.05%) had a CO-RADS score of six, and only 150 (6.40%) had CO-RADS score of four. The CT severity score was normal in 147 (6.27%), mild in 724 (30.90%), moderate in 903 (38.54%), and severe in 569 (24.29%) participants. The CRP levels were moderate in 1200 (51.22%) and severe in 428 (18.27%) participants. The mean ferritin, D-dimer and interleukin-6 (IL-6) levels were 321.83 ± 266.42 ng/ml, 1.51 ± 0.85mg/l, and 323.05 ± 95.52pg/ml, respectively. The mean length of hospital stay was 10.25 ± 6.52 days. Most of them (1926 out of 2343, 82.20%) survived, and nearly 417 out of 2343 (17.80%) died. Out of 2343, 569 participants had severe CT severity scores, out of which 205 (36.03%) died, and 364 (63.97%) participants survived. Conclusion A positive correlation was found between CT severity scoring on HRCT thorax and inflammatory markers with COVID-19 related mortality and can be used in early diagnosis and timely management of COVID-19 positive patients.
ABSTRACT
The significant growth of Block chain technology has increasingly attracted the attention of different industries. At present every nation is preparing itself to fight against the humanitarian emergency of COVID 19 which have led to risk of lives of the frontline workers. Around the world steady progress is being made to increase the connectivity of health care infrastructure. Every nation is working hard towards making infrastructure available to tackle the communicable diseases and prevent further emergence of pandemic like this in future. Several technologies are being used to combat COVID 29 such as artificial intelligence for research, 5G to increase information transmission speed, and more. To prevent the health workers from getting infected it is required to take special precautions while providing treatments to the infected patients. With rapid increase in number of cases of Covid19 infected patients there is a huge demand for the Personal protective equipment (PPE) kits - a protective shield for the health workers, all over the world. Increasing demand poses various challenges like malpractices of black marketing, circulation of cheaper and sub standardized commodities and subjective price hike. Most of the malpractices are impacting the sale of these kits as well. Block chain technology can play an important role in helping governments and institutions respond to COVID-19 by integrating with healthcare and supply chains. This paper compares the current PPE kit supply chain management system and proposes a block chain based approach coupled with smart contract application to provide transparency and efficiency in PPE kit supply chain management. © 2020 Common Ground Research Networks. All rights reserved.
ABSTRACT
Agriculture is one of the major sector of Indian economy and Covid-19 pandemic condition has made an adverse impact on overall sector. The availability of labour under the social distancing constraint has disadvantaged the operations in many segments. In such a case, the need is to go for a compatible, sustainable and efficient method to make farming and irrigation easy in means of all the preventive measures issued by the government to survive the pandemic Covid 19. This paper highlights on the Smart farming which focuses on gathering the big data on cloud with the help of Internet of things (IOT) for tracking, monitoring and evaluating the data operation. This advanced technology will contribute towards upgrading the farming activities. © 2021 IEEE.
ABSTRACT
Light and electricity has turned out to be the key part of every individual life. Illumination technology is getting used in different aspects of energy saving and improvises the aesthetic look of the area under the impact of light source. Conventional operation has to be manually ON or OFF, as per our need which means it requires our touch. But in this situation of COVID-19, it has become essential to use smart lighting system technology, because it may not be safe to touch the light switches every time in some places, public areas like offices and hospitals. This major problem can be resolved by using smart lighting system as it is totally based on sensors. In this, LED lights are used to improve the impact of effectiveness. Compared to normal lighting system, the smart lighting system is highly efficient and easy to control. It also saves electricity units consumed. The input of smart lighting system can be either solar panel or conventional grid supply. Use of solar panel involves utilization of solar renewable source. Therefore, the power from the grid dependence is minimized. As it uses solar panels, it can be used in rural areas where there is scarcity of electricity or not yet reach. As per the requirement, even grid supply can be used. In smart lighting system light can be remotely controlled so unnecessary use of power is reduced to some extent, and this makes the system more useful. This paper focus on the reduction of the overall power usage, as well as includes new features with technology interface. © 2021 IEEE.