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Purpose The purpose of this research is to eliminate the problems like modification of data related to patient without patient’s consent, management of patient's profile and any type of miscommunication between the specialist. Design/methodology/approach A novel approach is designed to overcome the problem of disease overlapping. To this end, Blockchain technology is utilized due to its numerous benefits. Findings The simulation of the model is done in R-studio, and the results are determined for the difficulty level in terms of time taken to create specific block. The outcome showed the effectiveness of the proposed Blockchain technology. Originality/value The approach discussed in this article is a novel approach that shows the effectiveness of Blockchain technology with modification of patients’ data without his/her will, management of patient profile with latest data, and elimination of any type of miscommunication between the specialists.

PCR (Polymerase Chain Reaction) tests are used as a standard test for the COVID-19, which is having a lot of issues. For finding the exact results using the PCR testing technique,

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Abstract-There is lot of work done in prediction of the fault proneness of the software systems. But, it is the severity of the faults that is more important than number of faults existing in the developed system as the major faults matters most for a developer and those major faults needs immediate attention. As, Neural networks, which have been already applied in software engineering applications to build reliability growth models predict the gross change or reusability metrics. In which majority of faults are found in a few of its modules so there is a need to investigate the modules that are affected severely as compared to other modules and proper maintenance need to be done in time especially for the critical applications. In this present work, hybrid fuzzy-Genetic Algorithm and fuzzy clustering based technique to be studied. Fuzzy clustering Based techniques are also discussed for the comparative analysis in order to predict level of impact of faults in NASA's public domain defect dataset. Predicting faults in the software life cycle can be used to improve software process control and achieve high software reliability. The results show that when the best prediction techniques are evaluated.Index Terms-Neural network, software faults, software metric, fuzzy clustering, decision tree, k-means, software quality.

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Healthcare is an application where the Wireless Body Area Network (WBAN), the emerging field of Wireless Sensor Network (WSN), can give assistance to the person in case of detection of abnormal activities of the human body without demanding the presence of the doctor. The small-sized sensors can be deployed for continuous monitoring of the physical activities of the human body. In the case of abnormal activity, the sensors will alert the person as well as share the data with the health expert. The information to be sent is very critical so the routing nodes selection must be done in such a manner that the malicious nodes will not get the information. There are various factors which we can count as the selection parameters for taking a node as part of the route. The Trust of the sensor node is very important as if the node is not trustworthy the chances of delivering correct data to the destination node are very less. This may lead to a threat to a person’s life. In this paper we are presenting a routing algorithm which will count the trust of the node as an important factor and update the path if it found any malicious node in between the route